CRM (customer relationship management) platforms, Automation, & Autonomation scenarios

0. Introduction

This paper tries to envision the future of CRM customer relationship management platforms, automation, and “Autonomation” scenarios. This paper does not propose the strategies to build customer relationships nor about the ways that a CRM platform can be utilized to attract more customers or the ways it may help a business to attract more leads. This paper assesses the platforms and features to understand what could be the features of a future CRM software.

The timeframe of this research covers the near future, which is the next three years from the date of writing this paper.

Keywords: CRM, Autonomation; Jidoka, Automation, Autonomous Smart-Machines, Cognitive, Cognitive-Computing, Internet of Things, IoT, Robot, Robots, Cryptocurrencies, Crypto, Crypto-based, Fin-Tech, Financial, Transaction, Financial Transactions, Smart, Machine

1. Literature Review

1.1 Literature Review-Professional/Market sources

A CRM application features in academia are not defined as updated as in the professional world (market) and in real-life scenarios. To extract the list of CRM primary features, besides academic sources, we have to look into the professional world and real-life scenarios. These features are currently offered by top CRM apps companies and the ones which are mainly used and frequent and known on the internet.

CRM Apps have been evolving to be more efficient, user-friendly, and, most importantly, be the frontier and initial one offerings the best features all in a professional, competitive, but less academic environment. Proceeding with the data-gathering steps and extracting processes, a few CRMs come for in our list of the most common CRM apps on the web; deep web searching, data crawling, extracting, and filtering the results coming out of multiple search engines like Google, Bing, Yahoo, DuckDuckGo, and Yandex. The Apps were reviewed to extract the CRM features and what is missing regarding the integration and implementation of the automation, and Autonomation (if there exists).

The first popular CRM is Zoho. Zoho CRM’s notable features that are automated or have automation integrated are automated email campaigns, marketing operations, automatic import of data, all based on Zoho CRM’s marketing automation tools, which help running campaigns efficiently and to improve the ROI. Zoho Automation in building web-to-lead forms, capturing information about the visitors, and push the data directly into Zoho CRM. Zoho involves sales, marketing, and operational automation.

The next CRM to address is Bitrix24 CRM. Bitrix24 CRM automation is integrated into marketing, workflow, email, call-center features.

The third CRM on the list is Complexica’s Touchless CRM, which helps the company with customer data, interaction history, and a variety of reports, alerts, and notification. It relies on Artificial Intelligence to monitor the user, analyzing their plans, tasks, and executed activities, then automatically updating the relevant customer records. Artificial Intelligence can be used for the optimization of sales, marketing, & supply chain decisions. The platform is scalable and modularised. The automation is integrated into the marketing campaigns, personalization of communications based on core-metrics, workflow automation, automatically send a personalized email and keeps Keep leads, prospects and close the loop on sales results optimization of ongoing digital marketing activity.

The fourth CRM to review is Pipedrive, which its Workflow Automation helps better multitasking and automation on sales-processes and adding the related activities updates alongside the pipeline.

The fifth CRM to mention is Lead Guerrilla CRM, which has automation mostly integrated into marketing.

The sixth CRM is Agile CRM’s, which its automation is also more about marketing automation, email marketing with newsletters, personalization, A/B testing. Some detailed examples are web popups email newsletters, autoresponders, automation on score leads, and segment contacts automatically based on email opens, links clicks, web browsing activity, custom tags, and more.

As studied in this section of the literature review, Most of the platforms rely on their contact management system as their main feature.

CRM software was designed to help sales and customer service professionals tracking their activities. Over time they added automation on logging all customer interactions, including the phone calls and all interactions; the automated features continued to Customer service automation (Chatbot) and automated campaigns. Currently, more than before, We can see more overlaps in features of marketing automation software and CRM software, which were initially designed to focus more on Sales and customer services. Most current CRM apps offer marketing automation, periodically data measuring data, campaign performance, and Automated lead nurturing.

Most apps offer the marketing part automated and not Autonomated. Marketing automation in a CRM app brings more control when integrated with other elements of CRM. It is the primary automated feature: of all the apps reviewed above. In none of the earlier mentioned apps, the term Autonomation nor its concept in a CRM system has mentioned.

1.2 Literature Review-Academic sources

For the purpose of the literature review, I’ve done a deep web-search, data-crawling, extracting, and filtering the results coming out of multiple research sources such as Google Scholar, JSTOR using Mendeley and Endnote beside search-engines like Google, Bing, Yahoo, DuckDuckGo, and Yandex utilizing DevonAgent pro. Following that, I extracted and categorized the brief of papers according to their concept related to the terms used in this research; CRM features and what is missing regarding the integration and implementation of the automation and Autonomation (if there exists).

Relying on the online search engines and the most notable research portals, at the time of writing this paper, there is no research on the combination of the CRM features and Autonomation in the academic world. Internationally “automation is more recognized than Autonomation and search engines will suggest the automation instead of Autonomation. Searching Google scholar suggests to us “CRM Automation” instead of “CRM Automation.” For example, as can be seen in the image below, when we search Google Scholars for the term “Autonomation,” the search engine suggests “Automation” instead.

Figure 1. Google scholars search results on the term “CRM Autonomation” (2020)

After in-depth research on academic portals and libraries, I found the following studies in academia most relevant to the intersection of the CRM features, automation, and Autonomation.

Implementation

Tanner, J., and others (2005) discussed how the implementation of (CRM) strategies had gained its importance with many implications for sales-intensive organizations. The CRM strategies, analytical CRM, and operational CRM have been discussed. My paper fills the gaps of knowledge where we want to know how the implementation of some of the common CRM usage and strategies can be utilized with automation and Autonomation.

Integration and Utilization

Saini, A, and others (2010) studied the challenges for the integration and utilization of the CRM technologies into the marketing processes to improve the business activities’ performances. Their proposed model reflects the key drivers for higher CRM performance. Their model focuses more on business-to-business rather than business-to-consumer relationships. Their study includes the central concepts, such as utilization, and top management championship practices, CRM knowledge, employee IT skills, and the ways to impact strategic utilization through buy-in and expertise. There is no direct categorization of CRM features in this study but the utilization of strategies related to some features of a better CRM.

CRM strategy, analytical CRM, and operational CRM

Tanner, J. (2005) says technology advancement brought better customer tracking, more robust knowledge management, and direct customer communication. CRM strategies gained their importance more than ever for sales-intensive organizations. In his paper, the Implications of CRM strategy, analytical CRM, and operational CRM are discussed, particularly in terms of research opportunities. This paper investigates the edges of better CRM features according to available strategies.

Operations & Technology

Lynn Jurewicz and Todd Cutler (2003) emphasized more on technology, particularly on specific elements of operations in which it makes sense for public libraries to automate notification of new programs, services, materials, and calendars. Those, as mentioned earlier, are the only focused areas on automation. The article includes project automation grounds, based on reasons such as higher accuracy, convenience for staff and users, portable access via the Web, and many similar improvements. This paper analyzed the current CRM operations and the linkings to desired improvements in the defined area, such as a library.

Environments and the operational CRM and Automation

Budiardjo, E, and others (2017) assessed the CRM in the higher education environment and supposed the “higher education environment” as a “business environment” where customers are students and graduates. They tried to classify the business processes and the feature groups into operational, collaborative, and analytical social CRM. They discussed how operational CRM, which consists of marketing automation, sales-force automation, and service automation, has to deal with automation. Their viewpoint is different than the view that is going to be mentioned in my article with the focus on Autonomation and machine cognition. I consider these parts as gaps that overtime needed to be filled by Autonomation scenarios besides the current automation scenarios.

Consumer world vs. the enterprise world automation

Clara Shih (2016) initially started with a comparison of the ways data would be handled in the consumer world against the enterprise world. She mentioned that retailers’ data real-time analyses help them predict purchasing behaviors and optimize understanding which products have to be available, on the other side, in the enterprise world, data may traditionally and manually being entered into database systems such as customer relationship management software. At the time of writing the paper, she declared that CRM had not changed much since its origin in the 1990s, and Artificial intelligence, decision-support algorithms, and the predictive data-driven suggestions help bringing more focus on the most important matters, better improvements, and productivity. She adds that machine learning and predictive data engines made automation possible by setting the majority of sales reps frequent tasks, making the interaction between reps and customers toward more digital reporting, and concentrating on the effective factors and weak-points. Today’s automated, predictive world breaks the limitations of traditional CRM. Predictive analytics plays a significant role in the next CRM systems. She believes CRM isn’t dead, but reps will halt using it unless it can get smarter.

CRM Primary functions & Automation

Zajačko I. and others (2019) said that CRM systems in cases of having hundreds, thousands, or millions of customers should facilitate recognizing customer’s wishes, needs, and preferences adding appointment notes, important customer information, and relevant documents. They discuss the primary function of CRM systems is to enable individual customers to understand, tailor the offerings according to their needs and wishes, know, and manage their value for society. He adds automation of the business processes, such as logistics or human resource management comes with the automation of customer contact.

Features & Profitability

Kim, S. (2011) says in spite of the fact that companies have spent lots of money to implement CRM technologies, many have not reached satisfactory results on their CRM implementations. In this study, she mentioned some strategies and the impact of CRM investments on profitability. The relevance of this article is about the central CRM features leading to the profitability of a firm. The first feature under review is the marketing feature.

Autonomation definition & control

David Romero (2019) paper is one of the most relevant ones to my research literature review. His paper proposes Jidoka (autonomation-automation with a human touch) as the main guiding principle for SMEs’ digital transformation. However, the concept of Autonomation has been introduced as its very old and early definition. The paper explains the continuous increase of automation and intelligence levels happens in an economic, social, and technological sustainable way. The writer explained how the dual nature of Jidoka is missing; as an “automation approach” and also a “learning system” that brings improvements and the efficiency to manufacturing processes meanwhile developing the workforce skills needed to develop and/or adopt advanced automation solutions. The paper continues to this point that the developments of automatic control systems in the Industry 4.0 era can be achieved through human-machine mutual learning characterized by cyber-physical-social interactions in this way, sustainable higher levels of automation and intelligence. It also adds that Human operators need to be aware of the processes that are being automated; this leads to consistent, proper, and continuous updates of information and, consequently, the improvements of the processes and evolvement of digital technologies. It is briefed in the following sentence, “Incorporating human learning, gives automation its human touch.” This is the point where the article halted describing the evolvement of Autonomation. In my paper, I try to accomplish the modern definition of Autonomation and its connection with cognition, which is not only limited to humans and machines but the machines themselves and the self-training of them.

Autonomation

Lastly, I want to review the literature that I wrote in 2018 in a continuation of researching about Autonomation, cognition of Robots, Cryptocurrency-based, IoT. It described how a machine with cognition and power of human-like processing in any zone of life and level of human activities could be done autonomously. The modern definition of the Autonomation and autonomous systems, Machines cognition (Soul) have been mentioned and well-defined and mentioned in that paper.

Results

Reviewing the literature, Most of the definitions of Autonomation refer back to the definition used by Toyota. However, they are mostly in the production environment. There is not an article defining the relating the cognition to Autonomation and linking that to CRM systems. Secondly, The reviewed academic papers suggest the importance of the better CRM systems is about how they deal with data and predictive analysis of the data given manually or automatically kept in those systems. Even regarding CRM automation, the previous papers did not assess each feature of CRM individually and applied and assessed the automation scenarios in the marketing phase. The solution would be the assessment of the CRM features categorizing them and assessing the possible automation and autonomation scenarios on that. With this research, I try to fill the gaps of what those earlier mentioned papers sources missed to describe or introduce in their papers regarding the CRM features, and also add the new features which are in professional and enterprise environment, but not mentioned in the academic environments. Lastly, I give the latest understanding of the definition of the Autonomation and cognitive systems and its relation with the next or more advanced CRM systems and the ways it is connected to the features of CRM systems.

2. CRM

What is CRM?

CRM stands for customer relationship management. Today’s top CRM applications are usually structured in three forms; in the cloud, e.g., Salesforce, Google CRM (G-Suit), a combination of the cloud-based and desktop/mobile applications (e.g., openCRX, Daylite) or custom ones by developments/customizations done by companies; developing in-house CRM apps or by asking for the development of the customized ones.

3. CRM Applications

What can we do with the CRM application?

The activities of CRM applications can be categorized into four, relying on four fundamentals; sales, service, support, and quality. Business entities sell products or offer services to customers. Consequently, the support comes, and after, the entities maintain the procedure to understand if they are doing okay and if the customer is happy doing business with that entity. This is a cycle of convergence and divergence toward betterment and quality increase. That is a way that businesses do maintain their activities.

Most of the CRM applications offer the following features or have them integrated in a way; calendar, projects, tasks & to do(s), contacts section, groups, emails management (archiving, extracting, etc.), email marketing, trade/business panel/pipelines, information-center, integration/add-ons, Knowledge-base/tutorial/training, files/documents sections, and followups panel. Each CRM has different features and, of course, different costs or pricing. The cloud infrastructure that the platform is built on and the development time spent on features will mostly affect the pricing. For in-house made CRMs, the pricing is affected more by the development costs rather than the infrastructure costs. Choosing what the user needs and which CRM to choose, on a macro level, depends mostly on the size of the company, whether if it is a small, medium, large-sized enterprise or for a self-employed person.

4. Automation

The second term is Automation; Automation is simply to make anything “automatic.” It is an old-fashioned way of describing and defining the rules, patterns for different systems to make things automated. Merriam-Webster’s defines automation as “the technique of making an apparatus, a process, or a system operate automatically.” In the state of being automatic, the human-beings, the human factor, is very important. Because the human will start to define the patterns for the machine to make them automatic, if there is no human, machines will not do these things on their own. Humans have to tell them what to do, how to do, and when to do to make tasks automated and make progress in a project, setting a path forward.

5. Autonomation

The next term is “Autonomation.” This term was utilized by Toyota. In Japanese, the equivalent word for that is “Jidoka.” So what does it mean? For the first time that I conduct in-depth research about this term (2017), I searched the first pages and indexes utilizing online search engines like Google and other general online dictionaries; there was be no tangible result for this term. Still, if you search on technical dictionaries, mostly it will redirect to results referring to the definition practiced by Toyota. Japanese holds three alphabet systems Hiragana, Katakana, and Kanji. Logographic kanji are adopted Chinese characters and were influenced by the Chinese. Autonomation is defined in Hiragana. From 自 (Hiragana: じ, Ji, “auto”) and 退かす (Hiragana: どかす, dokasu, “to remove”). According to this definition, automation and humans are the elements of autonomation. The manufacturing process can be an automated process, producing a product just after another. When we have human supervision in the manufacturing process, then we will have autonomation. It means processes are automatic, but humans will find the issues if this system does not function well in automatic order, so there is a human who finds the possible issues and will fix them. The aforementioned is the old definition by Toyota, but nowadays, with the fourth Industrial Revolution that we faced about three years ago (2017), these things have changed; human supervision is now replaced by the Machine’s cognition to understand and self-detect the issues.

6. Cognition & Soulification

What is the fourth Industrial Revolution?

Today, most of the people in the society and connected to the World Wide Web have heard of cryptocurrencies like Bitcoin, Robotics, and Artificial Intelligence. The next Industrial Revolution has been started at the co-current of AI (artificial intelligence), cryptocurrencies, and cognitive-science (Kourosh Maheri, 2017). By the end of this cognitive evolution, machines (robots) can think like a human, or they think the way that human wants them to think. For example, if a Human wants a machine to think like him/her, the human would do only the initial programming of the machine, the machine will learn the further steps by herself/himself. To differentiate between cognitive and non-cognitive machines, We call machines with cognition by the pronoun he/she. He or she (the robot) not automatically but autonomously will perform the process. At this point, we use autonomous systems; it means the machines will have the cognition (souls). Autonomation simply can happen by the Soulification of the Machines (giving life). Entities’ cognition, the cognitive processes by the human brain or machine’s hardware as the central processing units, are the sign of their soul (Kourosh Maheri, 2017).

7. Full Autonomation/Autonomous Chipsets

The fully autonomous devices are still under development. The human is not able to make chipsets/processors programmed for a full cognition of the machine yet. I have done an in-depth deep web search, crawling, and indexing, and different data extraction methods have been utilized through various search engines and news portals, research platforms to extract the list of the currently available and publicly announced autonomous machines which are developed or are under developments. The 15.7 Gigabytes of text has been analyzed. There are pieces of evidence and patterns of military, governmental, and private companies’ usage and development of cognitive chipsets. Still, their general usage is not happening at the time of writing this article. There is no evidence (signal) promising a release of cognitive chipset technology for public usage in the near future (three years), but a gradual implementation in autonomous machines.

8. Minimum Autonomation/Machine’s Cognition

In the near future, in the timeframe of three years, we will have machines with a minimum of the human cognition for full autonomation, which (who) can partially think like humans to get things done autonomously. The signals have been extracted in my (2017) foresight research on Condition and autonomous machines. To make a fresh conclusion and include the recent results, another recent in-depth web search and data extraction, as explained in the previous section, was done. Considering the researches I have conducted, at this point, I define autonomation as a state where a machine or device is capable of making a decision; a robot can make a decision or analyze the data, like any living creature.

9. CRM Features

Until now, the three terms CRM, Automation, and Autonomation have been discussed. At this point, we are going to see what could be near-future scenarios of future CRM systems in terms of automation. The essential features of every CRM are about contacts, projects, and tasks. There are some additional features like opportunity management, quote management account management, finances, integration with 3rd part platforms, and reports. Every CRM system has a few basics and most useful features as below:

10. Contact/account management and subscriptions

One of the features of every CRM is the contact section. Contact management is simply about the information of the customers and the connections to them. Account management is when businesses deal with suppliers. Businesses usually have their own partners. The account management section of a CRM application is covering the partners. Contact management, account management, subscriptions can be autonomated, but they will be less likely to be autonomated. The reason is that in near future machines will not have enough cognition to decide about each individual contact. As for example, the cognition of the machine can not think and find a plausible customer and decide if a person is a promising customer to add it automatically to its database (autonomous circle of processes). Still, machines are able to find patterns as for example, patterns of which contact can be a customer.

11. Time/Task/Calendar/Projects:

The next important part of the CRM is about time; it is about the tasks, project, calendar, events, almost anything which is related to time and scheduling. Considering a near-future timeframe, the only element among those mentioned above, which can be autonomated, is recurring events. Predictable things, then they can be autonomated. An autonomation initially can happen in a “predictable scenario.” For example, when the machine can predict a scenario and make a decision relying on the machine’s cognition; consequently, a machine can schedule the tasks (set the jobs) as ABCD; make it autonomated. Above is plausible when a machine can think about what can be predicted.

12-Sales Process

The next part to discuss is the “sales process,” which can be automated but not fully autonomated. A good example is Amazon’s sales processes and approaches in its warehouses, which are automated but not fully autonomated, relying on the information extracted by me in Data-Crawling and extraction process explained before.

13. Invoicing

Invoicing can be fully autonomated. Machines have enough condition to process the autonomous invoice generating. The format, context, and patterns of the invoices make them highly predictable.

14. Reports

Although the context of the reports is usually prepared as templates by the developer and the content may have been according to the patterns, but the reports requests and generation cannot be autonomated. The processes on reports may need manual actions or confirmation. The C-level and the people in charge may need to decide on the type of report and the actions related to them. The machines may recognize the patterns of the previous request but can’t process these and decide to request or generate a specific kind of report. As an example, a CEO at a point of time may need a specific type of report because maybe she/he may need a specific term that the robots can’t decide for her/him.

15. Support

The next part is about support. Suppose that, when a customer visits a website, she/he faces a popup message asks how the support person, which is a bot, can help her/him; people may think of it as another automated reply by a bot. This scenario of an automatic chatbot is widely used in companies to decrease their staff costs. It is not convenient, helpful, pleasant for some people. Customers ask for human attention; it even can be a reply by ones who think like humans, entities who are responsible and attentive; attention, care, the human connection are the main three necessitated qualities that customers expect from the support team. General autonomous assistants machines are among the rare machines which may bring the feeling of human connection, interaction, and the human touch, but it would not be extensive, and it’s not plausible for public usage within the near-future timeframe.

16. Knowledge-base

As we understood earlier, a full Autonomation may not happen in regard to decisions on mechanical activities; The next section that can be totally autonomous is decision-making, which is according to the patterns on the predefined data; the knowledge-base in CRM platforms. The database that a user can search for her/his questions. The reason for that is the database interactions are mostly about inputs and outputs, patterns, whether by typing or by voice or any means of searching for a keyword. The user fills a field, and it will give her/him the data, the outputs. For the near future timeframe, the human can reach a fully autonomated knowledge-base receiving and sending the information based on the user inputs and needs.

17. Training

The next section of this article is about training. Following installing a CRM, the user falls in a learning curve. Like any other application, it takes some time to get used to that CRM software. The CRM applications’ first launch usually comes with a notification/popup window describing the application and platform features, tips, tricks, and channels to contact the support team. The first issue is that it lacks the human interaction; very automatic, no human touch and care is involved. It is not that helpful to many people if they get it automatic. A user may need to call a consultant or support team to ask for help. They may prefer to pay for the support to get a task process done. Usually, the top-level people of the companies do not have enough time to search in the directory or archives to find the solution but prefer a direct method to reach a solution. Some of the training procedures are customized and designed to help the users; they are by contacting the user by email, phone, or else. The development team may contact the users asking how they feel about the platform and what features do they need to be added to future releases. It worthy of mentioning that the more customized the training process, the more intervention in the development process would be possible. When we talk of Customization and human-designed applications, the autonomation by machines is less likely to happen, especially talking a near-future time frame. Fully autonomated training is less plausible during the timeframe of the research.

18. Marketing/Creative content

Marketing needs C-level decision making. The C level (the CEO and the top level of people in the company) need to make a decision and confirm what should be the content of a marketing campaign. Machines currently cannot create creative content for a marketing campaign, although they can recognize the patters and send the relevant ads. But the cognition of the machines in a near-future time frame is less likely to be capable of producing creative content, Beside it is less likely that the top-level people in a company give the machines a full authorization to send the content that machines created based on their machines schedule, decisions and confirmations. However, the more the science develops, content creation by machines is gaining its more human-like quality, as for example, the music created by machines, although this is also more based on patterns rather than a creative output of a cognitive process.

Customers are less interested in receiving an automatically generated advertisement email based on their previous shopping patterns; there will be more rate of unsubscription. However, customized and human-made content is more appealing to customers. Quality content is the output of Human cognition and soul, and it will receive more attention even if it is short in two or three sentences; This could be something meaningful in the eyes of the customer, so it is more likely to receive a reply. The machines can’t perform a creative thinking process to create some campaigns and send them to people and lists. It may need a C-level decision and confirmation. The near future Autonomation is not plausible to happen.

19. Design, extensibility, integration with 3rd parties, add-on (s), plugins

Other elements of a CRM, such as the UI design (user interface), adding features, development, cannot be autonomated. UI designing needs creativity; the above, just like support, cannot be fully autonomated in the near-future timeframe. A manual action can be done by humans and relying on human creativity, which in the near future, it is less plausible to be entirely in the hands of machines. Development and extensibility are based on human decisions, whether when an entity, user, the team C-level, or else asks for a feature or decides to add remove, change.

20. Maintenance and Quality

Quality control, maintenance, and assessment are processes that need humans to decide and are relying on human logic and reasoning. They need a minimum of human cognition.

21. Inventory and Product Management

The product and inventory management in any CRM software can be automated by categorization and reports, but the management and decisions on the product or service cannot be autonomated. Data can be processed by machines, but which data and the means of the process need to be defined by a human.

22. Files & Documents

Documents and office files should be handled analyses and comprehended by humans as humans are the ones who rely on the information and need them most. Although Machines make automated decisions based on the data analyses and data extraction processes, Still the majority of cognition process is by humans, and the needs and requests will be from the human in the near future. The decision on access level also needs human thought.

23. Security

A top field of the future carriers is security; conglomerates top jobs cover the term “security.” Human factor holds its importance in security-related jobs as management and administration or specializations. There will be human decisions on access and human definitions of the access-levels. This field relies more on human cognition than machines for top-level decision makings. Security is about human intelligence, so machines again cannot have that job in their hand autonomously. The autonomous machines will be utilized to detect the data breaches and do the automated tasks to protect systems. The human will not rely on their cognition to give them control of the security systems for the next three years. Despite heavy usage of automation, the top-level decisions and operations and system-level security (system of Systems) will be in the hand of a human and will not be autonomated in the near-future.

24. Conclusion

24.1 Conclusion

Goal

This paper tried to envision the plausible future of CRM customer relationship management platforms, Automation, and “Autonomation” scenarios based on the current CRM apps features, technological market advancements and signals, and possibilities and also considering the cognition advancements of the Machines for a timeframe of the next three years.

Reviews

CRM application features in academia are not defined as updated as in the professional world (market), and real-life scenarios. I’ve considered the professional world and real-life scenarios to find the top and most known CRM apps companies. The result of my deep web search, data crawling, and classification of the ranking of the results pointed to the following apps; Zoho, Bitrix24, Complexica’s, Pipedrive Agile CRM. I studied the official resources for the features of the mentioned apps besides testing them again in trial/demo for the purpose of this study. The result indicates that all of the apps have one primary automated feature, and that is Marketing. In none of the earlier mentioned apps, the term Autonomation nor its concept in a CRM system has mentioned.

Secondly, I studied and investigated some academic sources for CRM automation. The previously published papers did not assess each feature of CRM apps and platforms individually nor studied automation scenarios of each feature except the marketing feature; As it has mentioned in a few of the reviewed papers, predictive scenarios play a significant role in the Automation of CRM systems. In none of the previous CRM researches, the term Autonomation and CRM somehow are linked. There is not an article defining the relating the cognition to Autonomation and linking that to CRM systems. With this research, I tried to fill the gaps of what those earlier mentioned papers sources missed to describe or to introduce in their papers regarding the CRM features. I have also added the features which are in the professional and enterprise environment but not mentioned in the academic environments. 

Autonomation Definition

At the time of writing the article, Most of the definitions of Autonomation referred back to the definition used by Toyota in the production environment. Considering the researches I have conducted, I gathered the concepts into one definition into ono and defined Autonomation as the modern definition of Autonomation as a state where a machine or device is capable of making a decision; a robot can make a decision or analyze the data, like any living creature. 

4th revolution and cognitive Chipsets

The fourth revolution is paralleled by scientific advancements of Fin-Tech (cryptocurrencies), Autonomation, Cognitive-Computing, developments in Robotics sciences, and the “Internet of Things” ecosystem. The next Industrial Revolution has been started at the co-current of AI (artificial intelligence), cryptocurrencies, and cognitive-science (Kourosh Maheri, 2017). By the end of this cognitive evolution, machines (robots) can think like a human, or they think the way that human wants them to think. We call machines with cognition by the pronoun he/she. He or she (the robot) not automatically but autonomously will perform the process. At this point, we use autonomous systems; it means the machines will have the cognition (souls). Autonomation simply can happen by the Soulification of the Machines (giving life). Entities’ cognition, the cognitive processes by the human brain or Machine’s hardware as the central processing units, are the sign of their soul (Kourosh Maheri, 2017).

Chipsets, Cognition, and Autonomation

I have done a deep web-search, utilized different data crawling, indexing, extraction methods through various search-engines and news portals, research platforms to extract the list of the currently available and publicly announced autonomous machines which are developed or are under developments. The 15.7 Gigabytes of text has been analyzed. There are pieces of evidence and patterns of military, governmental, and private companies’ usage and development of cognitive chipsets. Still, their general usage is not happening at the time of writing this article. There is no evidence (signal) promising a release of cognitive chipset technology for public usage in the near future (three years), but a gradual implementation in autonomous machines. The fully autonomous devices are still under development. The human is not able to make chipsets/processors programmed for a full cognition (human-Like) of the Machine yet. In the near future, in the timeframe of three years, we will have machines with a minimum of the human cognition for Autonomation of some processes, these machines which (who) can partially think like humans to get things done autonomously. Until 2023 machines will have limited cognitive capabilities compared to humans and consequently limited autonomated features. The signals have been extracted in my (2017) foresight research; “Envisioning the plausible scenarios of Cryptocurrency-based, IoT, transactions: cognitively computed by Autonomous Smart (Cognitive) Machines & aligned with an updated hierarchy of human needs.”

Predictability & Machine’s Cognition in Automation & Autonomation

Predictive scenarios play a big role in both Automation and Autonomation of CRM systems. “Predictability” has a big role in “automation” as the “Machine’s cognition” has in “Autonomation.” If the feature deals with predictive data inputs and processes, then Automation is more likely. In short, the Autonomation relies on Automation processed by the Machine’s cognition. Autonomation happens with the minimum of the Machine’s cognition. Whenever we have enough cognition of the machines to deal, run, process with a feature, then at that point, we have Autonomation of the Machine running the CRM application.

Creativity, Design & Autonomation

Creativity, customization, and designs by humans are the areas where, according to research timeframe, the Autonomation by machines is less likely to happen, especially talking a near-future timeframe.

In this paper, we have assessed the CRM features then categorized them. Then, possible automation and autonomation scenarios have been evaluated.

Lastly, The Table Below contains most of the CRM app features followed by the plausibility of automation and autonomation scenarios on each with a short explanation.

24.2 Table

Table 1

CRM app features followed by the plausibility of automation and autonomation scenarios (2020)

Level Features Automation Autonomation Why? (Until the Year 2023)
1.0 Contacts Management/Customer Segmentation/Call-center Partial No Entities may manually add a contact or opportunity; the future machines will Over the research’s time-frame, a Machine, can not manage the contacts the same as humans, make human-made changes, decisions, bring up the discussions, nor has the full authorization to do aforementioned on behalf of a human.
1.1 Subscriptions Yes No Viewing, managing, and maintenance of the list need human supervision.
1.2 Account Management/Partner Management Partial No Needs stakeholders’ decision to choose/add/remove partners/suppliers. Unpredictable situations are possible/Customization may be needed.
2.0 Calendars, Timesheets; Project, Tasks, To-Dos, meetings, and Calls Partial No Input would be done both autonomously and manually. However, until 2023, Most of the tasks will be added manually. Inputs & actions mostly should be defined by a human.
2.1 Events Appointment Scheduling Yes No May need human input
2.2 Recurring Events Yes Yes Predictable scenarios make the autonomation of recurring Events possible.
3.0 Sales Process Yes No Sales can not be a machine only process. (e.g., Sales Quotes)
3.1 Territory management Purchase/Point of Sale Partial No Manual input by the customer may be needed and also a manual transfer of the customer’s concern to a department. The customer may change the order details manually.
3.2 eCommerce Yes No Changes/Add-Ons for the platform may come by a human
3.3 Order Management/Quote Partial No May need human actions.
3.4 Accounting Yes No Manual returns/Exceptions will happen.
3.5 Payments/Expenses Yes No Manual payments would happen in cases and are very plausible. An automated purchase is possible, but an autonomated one which machine cognition decides on behalf of a human is less probable.
4.0 Invoicing/Invoices Yes Yes Automation is possible, although It is needed for all the other units to inform and submit any unpredicted change of the invoice terms manually. The format, context, and patterns of the invoices make them highly predictable, and the predictability makes the autonomation possible.
5.0 Reports, Dashboards/Key MetricsActivities History/Management/Forecasting Partial No Reports requests and generation cannot be autonomated. It is needed for all the other units to inform and submit any unpredicted change manually. Reports correctly are more for human supervision rather than the robotic cognition to rely on and decide accordingly.
5.1 Templates Pre-built reports and dashboards No No Human will make templates, dashboards; It is a human job.
6.0 Customer Support & Service/Helpdesk/Ticket management Partial No Urgent cases may come, or customized reply may be needed. General autonomous assistants machines are among the rare machines which may bring the feeling of human connection, interaction, and the human touch, but it would not be extensive, and it’s not plausible for public usage within the near-future timeframe.
6.1 Customer Self-Service Portal Yes No Users may face difficulties, and it may continue to request for human member support & followup.
7.0 Knowledge Base Yes Yes Autonomous chatbots. Although it needs all the other units to add/modify/ remove the content; knowledge-base receiving and sending the information based on the user inputs and needs
8.0 Training/Learning curve/Strategies Yes No The platform can be designed to put the users in a learning curve. It is also applicable for the customers as it can put them into a predesigned and predefined smart learning-procedure (e.g., by email, catalogs, media, etc.)
9.0 Marketing: Email Marketing/Campaigns Management/Creative content Partial No The platform can be designed to put the users in a learning curve. It is also applicable for the customers as it can put them into a predesigned and predefined smart learning-procedure (e.g., by email, catalogs, media, etc.). Total autonomation of the training process is not possible as machines will not reach that level of cognition to provide the learning to individuals according to personal qualities or a specific situation.
9.1 Opportunity Management/Lead Management Partial No It needs human decisions, manual input, and actions on the funnels. Lead>Contact>opportunity>Customer
9.2 Notifications (Apps, Emails, etc.) Partial No It may need human manual input.
9.3 Appraisal/assessment Yes No C-level or management decisions may be needed.
9.4 Website Yes No The connection between two platforms (CRM and Website) needs time to time human intervention. (e.g. Connections/Online appointments/Orders)
10.0 Design/Extensibility/API/Productivity Add-ons/Customization/configurability options/Equipments/Workflows/Mobility No No Adding manual changes of features and bringing creativity to the platform need human intervention. It eases the extensibility of the app. A human user should do customization (e.g., User Interface/Customizable Reports/Report Folders-Active users actions and Leaves). Modern CRM apps are hosted in the cloud and based on Software-as-a-Service (SaaS) model.
11.0 Maintenance & Quality Control No No A machine can only report the other units about the system deficits, not maintaining the processes such as delivery time or else. These processes need human supervision. They depend on human perception on the quality and human understandings of the advancements. These processes need a minimum of human cognition reasoning and logic for decisions.
13.0 Inventory Management/Product or service Lifecycle Management Partial No This part deals with the digital panel and also with the physical goods and logistics. These processes need human management to define timeframes. Management and decisions on the product or service cannot be autonomated. Data can be processed by machines, but which data and the means of the process need to be defined by a human.
14.0 Documents, File, Office, notes Partial No Machines make automated decisions based on data analyses and data extraction processes. Still, the majority of cognitive processes will be done by humans, and the needs and requests will be from the human in the near future. Data, files, and document management need human cognition; management, input, classification, arrangement, supervision, tagging, etc. Human interaction and actions are necessary to process office data. The autonomations would be less plausible.
15.0 Security Management Partial No A security specialist would be needed to analyze the system defects. the top-level decisions and operations and system-level security (system of Systems) will be in the hand of a human and will not be autonomated in the near-future.

References

Alfred, L. (n.d.). CRM Automation: The Ultimate Guide. Retrieved from https://blog.hubspot.com/sales/crm-automation

Budiardjo, E. K., Hidayanto, A. N., Meyliana, Fitriani, W. R., & Munajat, Q. (2017). Social CRM features identification for higher education. Journal of Engineering and Applied Sciences, 12(9), 2327-2333. https://doi.org/10.3923/jeasci.2017.2327.2333

Complexica Pty Ltd. (n.d.). CRM Automation. Retrieved from https://www.complexica.com/solutions/automating-crm

CRM with Marketing Automation. (n.d.). Retrieved from https://www.agilecrm.com/marketing

CRM with Marketing Automation: Zoho CRM Marketing Automation Software. (n.d.). Retrieved from https://www.zoho.com/crm/marketing-automation.html

Free CRM with Automation. (n.d.). Retrieved from https://www.bitrix24.com/uses/free-crm-with-automation.php

Jurewicz, L. & Cutler, T. (2003). High tech, high touch : library customer service through technology. Chicago: American Library Association.

Kim, S., & Mukhopadhyay, T. (2011). Determining Optimal CRM Implementation Strategies. Information Systems Research, 22(3), 624-639. Retrieved April 2, 2020, from www.jstor.org/stable/23015598

Maheri, K. (2018). Envisioning the plausible scenarios of Cryptocurrency-based, IoT, transactions: cognitively computed by Autonomous Smart (Cognitive) Machines & aligned with an updated hierarchy of human needs. https://doi.org/10.13140/RG.2.2.15398.98887

Marketing Automation – 1CRM: All-in-One CRM Software. (n.d.). Retrieved from https://1crm.com/marketing-automation/

Marketing Automation in CRM. (2020, February 13). Retrieved from https://www.rolustech.com/blog/marketing-automation-crm

Merriam-Webster. (n.d.). Automatic. In Merriam-Webster.com dictionary. Retrieved March 14, 2020, from https://www.merriam-webster.com/dictionary/automatic

Merriam-Webster. (n.d.). Automation. In Merriam-Webster.com dictionary. Retrieved March 14, 2020, from https://www.merriam-webster.com/dictionary/automation

Mitsubishi Research Institute, Inc. (n.d.). Retrieved March 14, 2020, from https://www.mri.co.jp/en/index.htm

Pipedrive Inc. (n.d.). Workflow Automation: Sales CRM Automation. Retrieved from https://www.pipedrive.com/en/features/workflow-automation

Romero, D., Gaiardelli, P., Powell, D., Wuest, T., & Thürer, M. (2019). Rethinking Jidoka Systems under Automation & Learning Perspectives in the Digital Lean Manufacturing World. IFAC-PapersOnLine, 52(13), 899–903. doi: 10.1016/j.ifacol.2019.11.309

Saini, A., Grewal, R., & Johnson, J. (2010). Putting market-facing technology to work: Organizational drivers of CRM performance. Marketing Letters, 21(4), 365-383. Retrieved April 2, 2020, from www.jstor.org/stable/40959687

Saurin, T. A., Formoso, C. T., & Cambraia, F. B. (2007, September 6). An analysis of construction safety best practices from a cognitive systems engineering perspective. Retrieved from https://www.sciencedirect.com/science/article/pii/S0925753507001270?via=ihub

Shih, C. (2017, April 21). Customer Relationship Automation Is the New CRM. Retrieved from https://hbr.org/2016/10/customer-relationship-automation-is-the-new-crm

Tanner, J., Ahearne, M., Leigh, T., Mason, C., & Moncrief, W. (2005). CRM in Sales-Intensive Organizations: A Review and Future Directions. The Journal of Personal Selling and Sales Management, 25(2), 169-180. Retrieved April 2, 2020, from www.jstor.org/stable/40472002

Toyota Research Institute. (n.d.). Retrieved March 14, 2020, from https://www.tri.global/

Zajačko, & I., K. (n.d.). International Scientific Journals of Scientific Technical Union of Mechanical Engineering “Industry 4.0”. Retrieved from https://stumejournals.com/journals/keyword/customer-relationship-management-crm

0. Introduction

This paper tries to envision the future of CRM customer relationship management platforms, automation, and “Autonomation” scenarios. This paper does not propose the strategies to build customer relationships nor about the ways that a CRM platform can be utilized to attract more customers or the ways it may help a business to attract more leads. This paper assesses the platforms and features to understand what could be the features of a future CRM software.

The timeframe of this research covers the near future, which is the next three years from the date of writing this paper.

Keywords: CRM, Autonomation; Jidoka, Automation, Autonomous Smart-Machines, Cognitive, Cognitive-Computing, Internet of Things, IoT, Robot, Robots, Cryptocurrencies, Crypto, Crypto-based, Fin-Tech, Financial, Transaction, Financial Transactions, Smart, Machine

1. Literature Review

1.1 Literature Review-Professional/Market sources

A CRM application features in academia are not defined as updated as in the professional world (market) and in real-life scenarios. To extract the list of CRM primary features, besides academic sources, we have to look into the professional world and real-life scenarios. These features are currently offered by top CRM apps companies and the ones which are mainly used and frequent and known on the internet.

CRM Apps have been evolving to be more efficient, user-friendly, and, most importantly, be the frontier and initial one offerings the best features all in a professional, competitive, but less academic environment. Proceeding with the data-gathering steps and extracting processes, a few CRMs come for in our list of the most common CRM apps on the web; deep web searching, data crawling, extracting, and filtering the results coming out of multiple search engines like Google, Bing, Yahoo, DuckDuckGo, and Yandex. The Apps were reviewed to extract the CRM features and what is missing regarding the integration and implementation of the automation, and Autonomation (if there exists).

The first popular CRM is Zoho. Zoho CRM’s notable features that are automated or have automation integrated are automated email campaigns, marketing operations, automatic import of data, all based on Zoho CRM’s marketing automation tools, which help running campaigns efficiently and to improve the ROI. Zoho Automation in building web-to-lead forms, capturing information about the visitors, and push the data directly into Zoho CRM. Zoho involves sales, marketing, and operational automation.

The next CRM to address is Bitrix24 CRM. Bitrix24 CRM automation is integrated into marketing, workflow, email, call-center features.

The third CRM on the list is Complexica’s Touchless CRM, which helps the company with customer data, interaction history, and a variety of reports, alerts, and notification. It relies on Artificial Intelligence to monitor the user, analyzing their plans, tasks, and executed activities, then automatically updating the relevant customer records. Artificial Intelligence can be used for the optimization of sales, marketing, & supply chain decisions. The platform is scalable and modularised. The automation is integrated into the marketing campaigns, personalization of communications based on core-metrics, workflow automation, automatically send a personalized email and keeps Keep leads, prospects and close the loop on sales results optimization of ongoing digital marketing activity.

The fourth CRM to review is Pipedrive, which its Workflow Automation helps better multitasking and automation on sales-processes and adding the related activities updates alongside the pipeline.

The fifth CRM to mention is Lead Guerrilla CRM, which has automation mostly integrated into marketing.

The sixth CRM is Agile CRM’s, which its automation is also more about marketing automation, email marketing with newsletters, personalization, A/B testing. Some detailed examples are web popups email newsletters, autoresponders, automation on score leads, and segment contacts automatically based on email opens, links clicks, web browsing activity, custom tags, and more.

As studied in this section of the literature review, Most of the platforms rely on their contact management system as their main feature.

CRM software was designed to help sales and customer service professionals tracking their activities. Over time they added automation on logging all customer interactions, including the phone calls and all interactions; the automated features continued to Customer service automation (Chatbot) and automated campaigns. Currently, more than before, We can see more overlaps in features of marketing automation software and CRM software, which were initially designed to focus more on Sales and customer services. Most current CRM apps offer marketing automation, periodically data measuring data, campaign performance, and Automated lead nurturing.

Most apps offer the marketing part automated and not Autonomated. Marketing automation in a CRM app brings more control when integrated with other elements of CRM. It is the primary automated feature: of all the apps reviewed above. In none of the earlier mentioned apps, the term Autonomation nor its concept in a CRM system has mentioned.

1.2 Literature Review-Academic sources

For the purpose of the literature review, I’ve done a deep web-search, data-crawling, extracting, and filtering the results coming out of multiple research sources such as Google Scholar, JSTOR using Mendeley and Endnote beside search-engines like Google, Bing, Yahoo, DuckDuckGo, and Yandex utilizing DevonAgent pro. Following that, I extracted and categorized the brief of papers according to their concept related to the terms used in this research; CRM features and what is missing regarding the integration and implementation of the automation and Autonomation (if there exists).

Relying on the online search engines and the most notable research portals, at the time of writing this paper, there is no research on the combination of the CRM features and Autonomation in the academic world. Internationally “automation is more recognized than Autonomation and search engines will suggest the automation instead of Autonomation. Searching Google scholar suggests to us “CRM Automation” instead of “CRM Automation.” For example, as can be seen in the image below, when we search Google Scholars for the term “Autonomation,” the search engine suggests “Automation” instead.

Figure 1. Google scholars search results on the term “CRM Autonomation” (2020)

After in-depth research on academic portals and libraries, I found the following studies in academia most relevant to the intersection of the CRM features, automation, and Autonomation.

Implementation

Tanner, J., and others (2005) discussed how the implementation of (CRM) strategies had gained its importance with many implications for sales-intensive organizations. The CRM strategies, analytical CRM, and operational CRM have been discussed. My paper fills the gaps of knowledge where we want to know how the implementation of some of the common CRM usage and strategies can be utilized with automation and Autonomation.

Integration and Utilization

Saini, A, and others (2010) studied the challenges for the integration and utilization of the CRM technologies into the marketing processes to improve the business activities’ performances. Their proposed model reflects the key drivers for higher CRM performance. Their model focuses more on business-to-business rather than business-to-consumer relationships. Their study includes the central concepts, such as utilization, and top management championship practices, CRM knowledge, employee IT skills, and the ways to impact strategic utilization through buy-in and expertise. There is no direct categorization of CRM features in this study but the utilization of strategies related to some features of a better CRM.

CRM strategy, analytical CRM, and operational CRM

Tanner, J. (2005) says technology advancement brought better customer tracking, more robust knowledge management, and direct customer communication. CRM strategies gained their importance more than ever for sales-intensive organizations. In his paper, the Implications of CRM strategy, analytical CRM, and operational CRM are discussed, particularly in terms of research opportunities. This paper investigates the edges of better CRM features according to available strategies.

Operations & Technology

Lynn Jurewicz and Todd Cutler (2003) emphasized more on technology, particularly on specific elements of operations in which it makes sense for public libraries to automate notification of new programs, services, materials, and calendars. Those, as mentioned earlier, are the only focused areas on automation. The article includes project automation grounds, based on reasons such as higher accuracy, convenience for staff and users, portable access via the Web, and many similar improvements. This paper analyzed the current CRM operations and the linkings to desired improvements in the defined area, such as a library.

Environments and the operational CRM and Automation

Budiardjo, E, and others (2017) assessed the CRM in the higher education environment and supposed the “higher education environment” as a “business environment” where customers are students and graduates. They tried to classify the business processes and the feature groups into operational, collaborative, and analytical social CRM. They discussed how operational CRM, which consists of marketing automation, sales-force automation, and service automation, has to deal with automation. Their viewpoint is different than the view that is going to be mentioned in my article with the focus on Autonomation and machine cognition. I consider these parts as gaps that overtime needed to be filled by Autonomation scenarios besides the current automation scenarios.

Consumer world vs. the enterprise world automation

Clara Shih (2016) initially started with a comparison of the ways data would be handled in the consumer world against the enterprise world. She mentioned that retailers’ data real-time analyses help them predict purchasing behaviors and optimize understanding which products have to be available, on the other side, in the enterprise world, data may traditionally and manually being entered into database systems such as customer relationship management software. At the time of writing the paper, she declared that CRM had not changed much since its origin in the 1990s, and Artificial intelligence, decision-support algorithms, and the predictive data-driven suggestions help bringing more focus on the most important matters, better improvements, and productivity. She adds that machine learning and predictive data engines made automation possible by setting the majority of sales reps frequent tasks, making the interaction between reps and customers toward more digital reporting, and concentrating on the effective factors and weak-points. Today’s automated, predictive world breaks the limitations of traditional CRM. Predictive analytics plays a significant role in the next CRM systems. She believes CRM isn’t dead, but reps will halt using it unless it can get smarter.

CRM Primary functions & Automation

Zajačko I. and others (2019) said that CRM systems in cases of having hundreds, thousands, or millions of customers should facilitate recognizing customer’s wishes, needs, and preferences adding appointment notes, important customer information, and relevant documents. They discuss the primary function of CRM systems is to enable individual customers to understand, tailor the offerings according to their needs and wishes, know, and manage their value for society. He adds automation of the business processes, such as logistics or human resource management comes with the automation of customer contact.

Features & Profitability

Kim, S. (2011) says in spite of the fact that companies have spent lots of money to implement CRM technologies, many have not reached satisfactory results on their CRM implementations. In this study, she mentioned some strategies and the impact of CRM investments on profitability. The relevance of this article is about the central CRM features leading to the profitability of a firm. The first feature under review is the marketing feature.

Autonomation definition & control

David Romero (2019) paper is one of the most relevant ones to my research literature review. His paper proposes Jidoka (autonomation-automation with a human touch) as the main guiding principle for SMEs’ digital transformation. However, the concept of Autonomation has been introduced as its very old and early definition. The paper explains the continuous increase of automation and intelligence levels happens in an economic, social, and technological sustainable way. The writer explained how the dual nature of Jidoka is missing; as an “automation approach” and also a “learning system” that brings improvements and the efficiency to manufacturing processes meanwhile developing the workforce skills needed to develop and/or adopt advanced automation solutions. The paper continues to this point that the developments of automatic control systems in the Industry 4.0 era can be achieved through human-machine mutual learning characterized by cyber-physical-social interactions in this way, sustainable higher levels of automation and intelligence. It also adds that Human operators need to be aware of the processes that are being automated; this leads to consistent, proper, and continuous updates of information and, consequently, the improvements of the processes and evolvement of digital technologies. It is briefed in the following sentence, “Incorporating human learning, gives automation its human touch.” This is the point where the article halted describing the evolvement of Autonomation. In my paper, I try to accomplish the modern definition of Autonomation and its connection with cognition, which is not only limited to humans and machines but the machines themselves and the self-training of them.

Autonomation

Lastly, I want to review the literature that I wrote in 2018 in a continuation of researching about Autonomation, cognition of Robots, Cryptocurrency-based, IoT. It described how a machine with cognition and power of human-like processing in any zone of life and level of human activities could be done autonomously. The modern definition of the Autonomation and autonomous systems, Machines cognition (Soul) have been mentioned and well-defined and mentioned in that paper.

Results

Reviewing the literature, Most of the definitions of Autonomation refer back to the definition used by Toyota. However, they are mostly in the production environment. There is not an article defining the relating the cognition to Autonomation and linking that to CRM systems. Secondly, The reviewed academic papers suggest the importance of the better CRM systems is about how they deal with data and predictive analysis of the data given manually or automatically kept in those systems. Even regarding CRM automation, the previous papers did not assess each feature of CRM individually and applied and assessed the automation scenarios in the marketing phase. The solution would be the assessment of the CRM features categorizing them and assessing the possible automation and autonomation scenarios on that. With this research, I try to fill the gaps of what those earlier mentioned papers sources missed to describe or introduce in their papers regarding the CRM features, and also add the new features which are in professional and enterprise environment, but not mentioned in the academic environments. Lastly, I give the latest understanding of the definition of the Autonomation and cognitive systems and its relation with the next or more advanced CRM systems and the ways it is connected to the features of CRM systems.

2. CRM

What is CRM?

CRM stands for customer relationship management. Today’s top CRM applications are usually structured in three forms; in the cloud, e.g., Salesforce, Google CRM (G-Suit), a combination of the cloud-based and desktop/mobile applications (e.g., openCRX, Daylite) or custom ones by developments/customizations done by companies; developing in-house CRM apps or by asking for the development of the customized ones.

3. CRM Applications

What can we do with the CRM application?

The activities of CRM applications can be categorized into four, relying on four fundamentals; sales, service, support, and quality. Business entities sell products or offer services to customers. Consequently, the support comes, and after, the entities maintain the procedure to understand if they are doing okay and if the customer is happy doing business with that entity. This is a cycle of convergence and divergence toward betterment and quality increase. That is a way that businesses do maintain their activities.

Most of the CRM applications offer the following features or have them integrated in a way; calendar, projects, tasks & to do(s), contacts section, groups, emails management (archiving, extracting, etc.), email marketing, trade/business panel/pipelines, information-center, integration/add-ons, Knowledge-base/tutorial/training, files/documents sections, and followups panel. Each CRM has different features and, of course, different costs or pricing. The cloud infrastructure that the platform is built on and the development time spent on features will mostly affect the pricing. For in-house made CRMs, the pricing is affected more by the development costs rather than the infrastructure costs. Choosing what the user needs and which CRM to choose, on a macro level, depends mostly on the size of the company, whether if it is a small, medium, large-sized enterprise or for a self-employed person.

4. Automation

The second term is Automation; Automation is simply to make anything “automatic.” It is an old-fashioned way of describing and defining the rules, patterns for different systems to make things automated. Merriam-Webster’s defines automation as “the technique of making an apparatus, a process, or a system operate automatically.” In the state of being automatic, the human-beings, the human factor, is very important. Because the human will start to define the patterns for the machine to make them automatic, if there is no human, machines will not do these things on their own. Humans have to tell them what to do, how to do, and when to do to make tasks automated and make progress in a project, setting a path forward.

5. Autonomation

The next term is “Autonomation.” This term was utilized by Toyota. In Japanese, the equivalent word for that is “Jidoka.” So what does it mean? For the first time that I conduct in-depth research about this term (2017), I searched the first pages and indexes utilizing online search engines like Google and other general online dictionaries; there was be no tangible result for this term. Still, if you search on technical dictionaries, mostly it will redirect to results referring to the definition practiced by Toyota. Japanese holds three alphabet systems Hiragana, Katakana, and Kanji. Logographic kanji are adopted Chinese characters and were influenced by the Chinese. Autonomation is defined in Hiragana. From 自 (Hiragana: じ, Ji, “auto”) and 退かす (Hiragana: どかす, dokasu, “to remove”). According to this definition, automation and humans are the elements of autonomation. The manufacturing process can be an automated process, producing a product just after another. When we have human supervision in the manufacturing process, then we will have autonomation. It means processes are automatic, but humans will find the issues if this system does not function well in automatic order, so there is a human who finds the possible issues and will fix them. The aforementioned is the old definition by Toyota, but nowadays, with the fourth Industrial Revolution that we faced about three years ago (2017), these things have changed; human supervision is now replaced by the Machine’s cognition to understand and self-detect the issues.

6. Cognition & Soulification

What is the fourth Industrial Revolution?

Today, most of the people in the society and connected to the World Wide Web have heard of cryptocurrencies like Bitcoin, Robotics, and Artificial Intelligence. The next Industrial Revolution has been started at the co-current of AI (artificial intelligence), cryptocurrencies, and cognitive-science (Kourosh Maheri, 2017). By the end of this cognitive evolution, machines (robots) can think like a human, or they think the way that human wants them to think. For example, if a Human wants a machine to think like him/her, the human would do only the initial programming of the machine, the machine will learn the further steps by herself/himself. To differentiate between cognitive and non-cognitive machines, We call machines with cognition by the pronoun he/she. He or she (the robot) not automatically but autonomously will perform the process. At this point, we use autonomous systems; it means the machines will have the cognition (souls). Autonomation simply can happen by the Soulification of the Machines (giving life). Entities’ cognition, the cognitive processes by the human brain or machine’s hardware as the central processing units, are the sign of their soul (Kourosh Maheri, 2017).

7. Full Autonomation/Autonomous Chipsets

The fully autonomous devices are still under development. The human is not able to make chipsets/processors programmed for a full cognition of the machine yet. I have done an in-depth deep web search, crawling, and indexing, and different data extraction methods have been utilized through various search engines and news portals, research platforms to extract the list of the currently available and publicly announced autonomous machines which are developed or are under developments. The 15.7 Gigabytes of text has been analyzed. There are pieces of evidence and patterns of military, governmental, and private companies’ usage and development of cognitive chipsets. Still, their general usage is not happening at the time of writing this article. There is no evidence (signal) promising a release of cognitive chipset technology for public usage in the near future (three years), but a gradual implementation in autonomous machines.

8. Minimum Autonomation/Machine’s Cognition

In the near future, in the timeframe of three years, we will have machines with a minimum of the human cognition for full autonomation, which (who) can partially think like humans to get things done autonomously. The signals have been extracted in my (2017) foresight research on Condition and autonomous machines. To make a fresh conclusion and include the recent results, another recent in-depth web search and data extraction, as explained in the previous section, was done. Considering the researches I have conducted, at this point, I define autonomation as a state where a machine or device is capable of making a decision; a robot can make a decision or analyze the data, like any living creature.

9. CRM Features

Until now, the three terms CRM, Automation, and Autonomation have been discussed. At this point, we are going to see what could be near-future scenarios of future CRM systems in terms of automation. The essential features of every CRM are about contacts, projects, and tasks. There are some additional features like opportunity management, quote management account management, finances, integration with 3rd part platforms, and reports. Every CRM system has a few basics and most useful features as below:

10. Contact/account management and subscriptions

One of the features of every CRM is the contact section. Contact management is simply about the information of the customers and the connections to them. Account management is when businesses deal with suppliers. Businesses usually have their own partners. The account management section of a CRM application is covering the partners. Contact management, account management, subscriptions can be autonomated, but they will be less likely to be autonomated. The reason is that in near future machines will not have enough cognition to decide about each individual contact. As for example, the cognition of the machine can not think and find a plausible customer and decide if a person is a promising customer to add it automatically to its database (autonomous circle of processes). Still, machines are able to find patterns as for example, patterns of which contact can be a customer.

11. Time/Task/Calendar/Projects:

The next important part of the CRM is about time; it is about the tasks, project, calendar, events, almost anything which is related to time and scheduling. Considering a near-future timeframe, the only element among those mentioned above, which can be autonomated, is recurring events. Predictable things, then they can be autonomated. An autonomation initially can happen in a “predictable scenario.” For example, when the machine can predict a scenario and make a decision relying on the machine’s cognition; consequently, a machine can schedule the tasks (set the jobs) as ABCD; make it autonomated. Above is plausible when a machine can think about what can be predicted.

12-Sales Process

The next part to discuss is the “sales process,” which can be automated but not fully autonomated. A good example is Amazon’s sales processes and approaches in its warehouses, which are automated but not fully autonomated, relying on the information extracted by me in Data-Crawling and extraction process explained before.

13. Invoicing

Invoicing can be fully autonomated. Machines have enough condition to process the autonomous invoice generating. The format, context, and patterns of the invoices make them highly predictable.

14. Reports

Although the context of the reports is usually prepared as templates by the developer and the content may have been according to the patterns, but the reports requests and generation cannot be autonomated. The processes on reports may need manual actions or confirmation. The C-level and the people in charge may need to decide on the type of report and the actions related to them. The machines may recognize the patterns of the previous request but can’t process these and decide to request or generate a specific kind of report. As an example, a CEO at a point of time may need a specific type of report because maybe she/he may need a specific term that the robots can’t decide for her/him.

15. Support

The next part is about support. Suppose that, when a customer visits a website, she/he faces a popup message asks how the support person, which is a bot, can help her/him; people may think of it as another automated reply by a bot. This scenario of an automatic chatbot is widely used in companies to decrease their staff costs. It is not convenient, helpful, pleasant for some people. Customers ask for human attention; it even can be a reply by ones who think like humans, entities who are responsible and attentive; attention, care, the human connection are the main three necessitated qualities that customers expect from the support team. General autonomous assistants machines are among the rare machines which may bring the feeling of human connection, interaction, and the human touch, but it would not be extensive, and it’s not plausible for public usage within the near-future timeframe.

16. Knowledge-base

As we understood earlier, a full Autonomation may not happen in regard to decisions on mechanical activities; The next section that can be totally autonomous is decision-making, which is according to the patterns on the predefined data; the knowledge-base in CRM platforms. The database that a user can search for her/his questions. The reason for that is the database interactions are mostly about inputs and outputs, patterns, whether by typing or by voice or any means of searching for a keyword. The user fills a field, and it will give her/him the data, the outputs. For the near future timeframe, the human can reach a fully autonomated knowledge-base receiving and sending the information based on the user inputs and needs.

17. Training

The next section of this article is about training. Following installing a CRM, the user falls in a learning curve. Like any other application, it takes some time to get used to that CRM software. The CRM applications’ first launch usually comes with a notification/popup window describing the application and platform features, tips, tricks, and channels to contact the support team. The first issue is that it lacks the human interaction; very automatic, no human touch and care is involved. It is not that helpful to many people if they get it automatic. A user may need to call a consultant or support team to ask for help. They may prefer to pay for the support to get a task process done. Usually, the top-level people of the companies do not have enough time to search in the directory or archives to find the solution but prefer a direct method to reach a solution. Some of the training procedures are customized and designed to help the users; they are by contacting the user by email, phone, or else. The development team may contact the users asking how they feel about the platform and what features do they need to be added to future releases. It worthy of mentioning that the more customized the training process, the more intervention in the development process would be possible. When we talk of Customization and human-designed applications, the autonomation by machines is less likely to happen, especially talking a near-future time frame. Fully autonomated training is less plausible during the timeframe of the research.

18. Marketing/Creative content

Marketing needs C-level decision making. The C level (the CEO and the top level of people in the company) need to make a decision and confirm what should be the content of a marketing campaign. Machines currently cannot create creative content for a marketing campaign, although they can recognize the patters and send the relevant ads. But the cognition of the machines in a near-future time frame is less likely to be capable of producing creative content, Beside it is less likely that the top-level people in a company give the machines a full authorization to send the content that machines created based on their machines schedule, decisions and confirmations. However, the more the science develops, content creation by machines is gaining its more human-like quality, as for example, the music created by machines, although this is also more based on patterns rather than a creative output of a cognitive process.

Customers are less interested in receiving an automatically generated advertisement email based on their previous shopping patterns; there will be more rate of unsubscription. However, customized and human-made content is more appealing to customers. Quality content is the output of Human cognition and soul, and it will receive more attention even if it is short in two or three sentences; This could be something meaningful in the eyes of the customer, so it is more likely to receive a reply. The machines can’t perform a creative thinking process to create some campaigns and send them to people and lists. It may need a C-level decision and confirmation. The near future Autonomation is not plausible to happen.

19. Design, extensibility, integration with 3rd parties, add-on (s), plugins

Other elements of a CRM, such as the UI design (user interface), adding features, development, cannot be autonomated. UI designing needs creativity; the above, just like support, cannot be fully autonomated in the near-future timeframe. A manual action can be done by humans and relying on human creativity, which in the near future, it is less plausible to be entirely in the hands of machines. Development and extensibility are based on human decisions, whether when an entity, user, the team C-level, or else asks for a feature or decides to add remove, change.

20. Maintenance and Quality

Quality control, maintenance, and assessment are processes that need humans to decide and are relying on human logic and reasoning. They need a minimum of human cognition.

21. Inventory and Product Management

The product and inventory management in any CRM software can be automated by categorization and reports, but the management and decisions on the product or service cannot be autonomated. Data can be processed by machines, but which data and the means of the process need to be defined by a human.

22. Files & Documents

Documents and office files should be handled analyses and comprehended by humans as humans are the ones who rely on the information and need them most. Although Machines make automated decisions based on the data analyses and data extraction processes, Still the majority of cognition process is by humans, and the needs and requests will be from the human in the near future. The decision on access level also needs human thought.

23. Security

A top field of the future carriers is security; conglomerates top jobs cover the term “security.” Human factor holds its importance in security-related jobs as management and administration or specializations. There will be human decisions on access and human definitions of the access-levels. This field relies more on human cognition than machines for top-level decision makings. Security is about human intelligence, so machines again cannot have that job in their hand autonomously. The autonomous machines will be utilized to detect the data breaches and do the automated tasks to protect systems. The human will not rely on their cognition to give them control of the security systems for the next three years. Despite heavy usage of automation, the top-level decisions and operations and system-level security (system of Systems) will be in the hand of a human and will not be autonomated in the near-future.

24. Conclusion

24.1 Conclusion

Goal

This paper tried to envision the plausible future of CRM customer relationship management platforms, Automation, and “Autonomation” scenarios based on the current CRM apps features, technological market advancements and signals, and possibilities and also considering the cognition advancements of the Machines for a timeframe of the next three years.

Reviews

CRM application features in academia are not defined as updated as in the professional world (market), and real-life scenarios. I’ve considered the professional world and real-life scenarios to find the top and most known CRM apps companies. The result of my deep web search, data crawling, and classification of the ranking of the results pointed to the following apps; Zoho, Bitrix24, Complexica’s, Pipedrive Agile CRM. I studied the official resources for the features of the mentioned apps besides testing them again in trial/demo for the purpose of this study. The result indicates that all of the apps have one primary automated feature, and that is Marketing. In none of the earlier mentioned apps, the term Autonomation nor its concept in a CRM system has mentioned.

Secondly, I studied and investigated some academic sources for CRM automation. The previously published papers did not assess each feature of CRM apps and platforms individually nor studied automation scenarios of each feature except the marketing feature; As it has mentioned in a few of the reviewed papers, predictive scenarios play a significant role in the Automation of CRM systems. In none of the previous CRM researches, the term Autonomation and CRM somehow are linked. There is not an article defining the relating the cognition to Autonomation and linking that to CRM systems. With this research, I tried to fill the gaps of what those earlier mentioned papers sources missed to describe or to introduce in their papers regarding the CRM features. I have also added the features which are in the professional and enterprise environment but not mentioned in the academic environments. 

Autonomation Definition

At the time of writing the article, Most of the definitions of Autonomation referred back to the definition used by Toyota in the production environment. Considering the researches I have conducted, I gathered the concepts into one definition into ono and defined Autonomation as the modern definition of Autonomation as a state where a machine or device is capable of making a decision; a robot can make a decision or analyze the data, like any living creature. 

4th revolution and cognitive Chipsets

The fourth revolution is paralleled by scientific advancements of Fin-Tech (cryptocurrencies), Autonomation, Cognitive-Computing, developments in Robotics sciences, and the “Internet of Things” ecosystem. The next Industrial Revolution has been started at the co-current of AI (artificial intelligence), cryptocurrencies, and cognitive-science (Kourosh Maheri, 2017). By the end of this cognitive evolution, machines (robots) can think like a human, or they think the way that human wants them to think. We call machines with cognition by the pronoun he/she. He or she (the robot) not automatically but autonomously will perform the process. At this point, we use autonomous systems; it means the machines will have the cognition (souls). Autonomation simply can happen by the Soulification of the Machines (giving life). Entities’ cognition, the cognitive processes by the human brain or Machine’s hardware as the central processing units, are the sign of their soul (Kourosh Maheri, 2017).

Chipsets, Cognition, and Autonomation

I have done a deep web-search, utilized different data crawling, indexing, extraction methods through various search-engines and news portals, research platforms to extract the list of the currently available and publicly announced autonomous machines which are developed or are under developments. The 15.7 Gigabytes of text has been analyzed. There are pieces of evidence and patterns of military, governmental, and private companies’ usage and development of cognitive chipsets. Still, their general usage is not happening at the time of writing this article. There is no evidence (signal) promising a release of cognitive chipset technology for public usage in the near future (three years), but a gradual implementation in autonomous machines. The fully autonomous devices are still under development. The human is not able to make chipsets/processors programmed for a full cognition (human-Like) of the Machine yet. In the near future, in the timeframe of three years, we will have machines with a minimum of the human cognition for Autonomation of some processes, these machines which (who) can partially think like humans to get things done autonomously. Until 2023 machines will have limited cognitive capabilities compared to humans and consequently limited autonomated features. The signals have been extracted in my (2017) foresight research; “Envisioning the plausible scenarios of Cryptocurrency-based, IoT, transactions: cognitively computed by Autonomous Smart (Cognitive) Machines & aligned with an updated hierarchy of human needs.”

Predictability & Machine’s Cognition in Automation & Autonomation

Predictive scenarios play a big role in both Automation and Autonomation of CRM systems. “Predictability” has a big role in “automation” as the “Machine’s cognition” has in “Autonomation.” If the feature deals with predictive data inputs and processes, then Automation is more likely. In short, the Autonomation relies on Automation processed by the Machine’s cognition. Autonomation happens with the minimum of the Machine’s cognition. Whenever we have enough cognition of the machines to deal, run, process with a feature, then at that point, we have Autonomation of the Machine running the CRM application.

Creativity, Design & Autonomation

Creativity, customization, and designs by humans are the areas where, according to research timeframe, the Autonomation by machines is less likely to happen, especially talking a near-future timeframe.

In this paper, we have assessed the CRM features then categorized them. Then, possible automation and autonomation scenarios have been evaluated.

Lastly, The Table Below contains most of the CRM app features followed by the plausibility of automation and autonomation scenarios on each with a short explanation.

24.2 Table

Table 1

CRM app features followed by the plausibility of automation and autonomation scenarios (2020)

Level Features Automation Autonomation Why? (Until the Year 2023)
1.0 Contacts Management/Customer Segmentation/Call-center Partial No Entities may manually add a contact or opportunity; the future machines will Over the research’s time-frame, a Machine, can not manage the contacts the same as humans, make human-made changes, decisions, bring up the discussions, nor has the full authorization to do aforementioned on behalf of a human.
1.1 Subscriptions Yes No Viewing, managing, and maintenance of the list need human supervision.
1.2 Account Management/Partner Management Partial No Needs stakeholders’ decision to choose/add/remove partners/suppliers. Unpredictable situations are possible/Customization may be needed.
2.0 Calendars, Timesheets; Project, Tasks, To-Dos, meetings, and Calls Partial No Input would be done both autonomously and manually. However, until 2023, Most of the tasks will be added manually. Inputs & actions mostly should be defined by a human.
2.1 Events Appointment Scheduling Yes No May need human input
2.2 Recurring Events Yes Yes Predictable scenarios make the autonomation of recurring Events possible.
3.0 Sales Process Yes No Sales can not be a machine only process. (e.g., Sales Quotes)
3.1 Territory management Purchase/Point of Sale Partial No Manual input by the customer may be needed and also a manual transfer of the customer’s concern to a department. The customer may change the order details manually.
3.2 eCommerce Yes No Changes/Add-Ons for the platform may come by a human
3.3 Order Management/Quote Partial No May need human actions.
3.4 Accounting Yes No Manual returns/Exceptions will happen.
3.5 Payments/Expenses Yes No Manual payments would happen in cases and are very plausible. An automated purchase is possible, but an autonomated one which machine cognition decides on behalf of a human is less probable.
4.0 Invoicing/Invoices Yes Yes Automation is possible, although It is needed for all the other units to inform and submit any unpredicted change of the invoice terms manually. The format, context, and patterns of the invoices make them highly predictable, and the predictability makes the autonomation possible.
5.0 Reports, Dashboards/Key MetricsActivities History/Management/Forecasting Partial No Reports requests and generation cannot be autonomated. It is needed for all the other units to inform and submit any unpredicted change manually. Reports correctly are more for human supervision rather than the robotic cognition to rely on and decide accordingly.
5.1 Templates Pre-built reports and dashboards No No Human will make templates, dashboards; It is a human job.
6.0 Customer Support & Service/Helpdesk/Ticket management Partial No Urgent cases may come, or customized reply may be needed. General autonomous assistants machines are among the rare machines which may bring the feeling of human connection, interaction, and the human touch, but it would not be extensive, and it’s not plausible for public usage within the near-future timeframe.
6.1 Customer Self-Service Portal Yes No Users may face difficulties, and it may continue to request for human member support & followup.
7.0 Knowledge Base Yes Yes Autonomous chatbots. Although it needs all the other units to add/modify/ remove the content; knowledge-base receiving and sending the information based on the user inputs and needs
8.0 Training/Learning curve/Strategies Yes No The platform can be designed to put the users in a learning curve. It is also applicable for the customers as it can put them into a predesigned and predefined smart learning-procedure (e.g., by email, catalogs, media, etc.)
9.0 Marketing: Email Marketing/Campaigns Management/Creative content Partial No The platform can be designed to put the users in a learning curve. It is also applicable for the customers as it can put them into a predesigned and predefined smart learning-procedure (e.g., by email, catalogs, media, etc.). Total autonomation of the training process is not possible as machines will not reach that level of cognition to provide the learning to individuals according to personal qualities or a specific situation.
9.1 Opportunity Management/Lead Management Partial No It needs human decisions, manual input, and actions on the funnels. Lead>Contact>opportunity>Customer
9.2 Notifications (Apps, Emails, etc.) Partial No It may need human manual input.
9.3 Appraisal/assessment Yes No C-level or management decisions may be needed.
9.4 Website Yes No The connection between two platforms (CRM and Website) needs time to time human intervention. (e.g. Connections/Online appointments/Orders)
10.0 Design/Extensibility/API/Productivity Add-ons/Customization/configurability options/Equipments/Workflows/Mobility No No Adding manual changes of features and bringing creativity to the platform need human intervention. It eases the extensibility of the app. A human user should do customization (e.g., User Interface/Customizable Reports/Report Folders-Active users actions and Leaves). Modern CRM apps are hosted in the cloud and based on Software-as-a-Service (SaaS) model.
11.0 Maintenance & Quality Control No No A machine can only report the other units about the system deficits, not maintaining the processes such as delivery time or else. These processes need human supervision. They depend on human perception on the quality and human understandings of the advancements. These processes need a minimum of human cognition reasoning and logic for decisions.
13.0 Inventory Management/Product or service Lifecycle Management Partial No This part deals with the digital panel and also with the physical goods and logistics. These processes need human management to define timeframes. Management and decisions on the product or service cannot be autonomated. Data can be processed by machines, but which data and the means of the process need to be defined by a human.
14.0 Documents, File, Office, notes Partial No Machines make automated decisions based on data analyses and data extraction processes. Still, the majority of cognitive processes will be done by humans, and the needs and requests will be from the human in the near future. Data, files, and document management need human cognition; management, input, classification, arrangement, supervision, tagging, etc. Human interaction and actions are necessary to process office data. The autonomations would be less plausible.
15.0 Security Management Partial No A security specialist would be needed to analyze the system defects. the top-level decisions and operations and system-level security (system of Systems) will be in the hand of a human and will not be autonomated in the near-future.

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