Artificial Intelligence: Redefining the Future of CRM

The new age technology Artificial Intelligence, apart from transforming various other industries, has also transformed Customer Relationship Management (CRM). On the same lines, Mr. Snehashish Bhattacharjee, Global CEO, Denave, talks about how the CRM landscape has changed over the years, the role of emerging technologies in improving efficiency of CRM software, and much more.

Excerpts:

How has the Customer Relationship Management (CRM) landscape changed over the years?

Since 1980s, we have observed a huge change in the realm of Customer Relationship Management. Earlier, it existed in the form of automated management of customers’ contact details but with the passage of time, it has definitely fallen into its desired alignment with sales representatives’ goals and business values.

Today, with the evolution of big data and cloud computing, CRM has undergone some major changes. While big data brings the huge pool of structured and unstructured data, cloud computing assists by leveraging integrated and scalable techniques.

Evolving technologies like Artificial Intelligence (AI) supported by Machine Learning (ML), Business Intelligence (BI) and Analytics are providing a 360-degree view of customer’s experience. This further aids various CRM softwares to be more effective and targeted in its approach. Gartner Report claims, “CRM software revenue to be the fastest moving software market with the growth rate of 16% in 2018, having tipped the topper database management systems (DBMSs) by the end of 2017, producing $39.5 billion in revenue.”

Please explain the role of emerging technologies in improving efficiency of CRM software/tools?

CRM tools have always been performing data analytics to map patterns and predicament trends, line up leads, improve efficiency and track customers. But certain emerging technologies dipping its toes into the world of business, are continuously polishing the efficiency of CRM software/tools. Let’s have a look at how this happens:

• With AI/ML playing an enhanced role coupled with social media proliferation, CRM tools has undergone revamp. While AI/ML aids in better predictive analytics, social media helps in bringing the customers closer to the business strategies in order to accomplish business goals (enhancement of customer experiences, boosting customer perseverance and objectifying ever-evolving customer needs).
• AI holds an abundant potential in boosting the output of CRM tools. It is quite obvious that the utmost requirement of AI is to see the holistic view of customer’s entire journey- ever since the time they became a prospect till the stage of retention.

Are we moving towards micro service-based business model spearheaded by AI integrated CRM tools?

AI is no longer considered to be a science fiction but an important tool that could change almost every aspect of our lives. It delivers solution at faster rate while simultaneously eliminating the natural factor of “human error” that is frequently considered unforgivable by customers. However, the purpose of its utilization for customer care is not to dehumanize the process but possibly treasure better and faster solutions, by reaching beyond the limitations of an actual employee.

Now, since focusing on CRM has become a vital outlook of companies worldwide, implementing AI solutions into it can actively improve productivity. Of course, AI eradicates the burden of menial tasks, which are often essential and must be accomplished at first try.

Also, there are some of the upcoming interesting applications of AI in CRM tools where few of them are in the experimental stage and others are in the planning stage. Thus, the entire vision perpetually is to construct a micro-service-based business model.

In reference to that, let’s have a quick view of a selection of predicted evolution that CRM software will witness as the leverage of AI becomes stronger.

Intelligent Automation: With the fusion of AI into CRM software/tools we will be able to restructure the workflow and automate the manual and iterative chores intelligently. Moreover, these models will be leveraged to predict customer behavior, evaluate sales funnel, cracking the possible deals and predicting revenue with maximum accuracy. No wonder, with such a huge chunk of information at disposal, it will be easy to presume the next steps and digitally nurture the leads to develop an interesting behavioural assumption of the customers. Let’s see how:

• AI technology is leveraged in those complex training models which deal in feeding customer pursuits, demographics and their sales records. Therefore, in coming years, these models will further be used in predicting the possibilities of customer’s purchase of products. As a result, it will also aid in the identification of potential customer segments for new products/schemes for marketing or sales functions with added accuracy.
• With the combination of ML processes, there will be a conversion in CRM transcription.
• AI will also intensify change in the predictability of the outcome of customer interactions, customer’s opinion, customer behavioural patterns, nature of transaction and market dynamics.

As a result, AI will supplement CRM to enhance and improve all the business chores and operations by heightening routine tasks, providing a virtual assistance to employees, progressing customer segmentation and prioritizing leads.

Data drilling appliance: AI incorporation with CRM will change entire customer interaction to AI led as an alternative to human intervention led. Consequently, it will reduce conversation sequences and will intensify customer satisfaction in a support or sales scenario. Few CRM predictions related to past interactions and responses are as follows:

• Products are the leading factors that connect with a particular profile of a customer. Therefore, CRM platforms will help to pre-empt customer satisfaction issues and also make customer support more predictive and pre-emptive.
• With a pre-work on previous purchase records related to the profile of the customer, CRM platforms can aid in prioritizing the potential customers amongst all and position them in an order to get contacted. End results will lead to higher productivity from the CRM users/agents on the ground.
• CRM platforms perform various roles and act as a personal assistant to the CRM Stakeholders at different levels. It works like agents/sales executives, program owners, budget proprietors, or decision makers.
• This entails pre-planning the day based on past trends, priorities identification on actions are taken/gaps in the present techniques or processes based on data inputs which are required to be readdressed on a prior basis. Eventually, it can eradicate the need for an intelligent business manager to lead the stakeholder's work schedule and priorities for deriving effective decisions.

Proficiency to guide beginners: AI enabled CRM tools will provide a training manifesto which will be driven with minutest human interaction and the on-the-job instead of post facto. It will substitute the need for on the floor training managers and provide prompt feedback on the jobs by witnessing divergence in potential outcomes, based on the situation.

Bots making life easy: Chatbots are our next best friends. In due course, with AI integration, they will be going to become more intelligent and integrated. This application will combine both past and dynamic data of customers sourced from clickstream, online actions and variant records. Supported by intelligence, it will be able to provide real-time advice for sales pitches and for course correction as well.

• Chatbots and Robotic process automation will aid the users who are related with known or similar issues in past, reducing the requirement for humans for L1 or L2 support.
• This automation can be demonstrated with more common sense understanding, reasoning and memories. As a result, this assistant will be able to forecast customer’s needs even in the dearth of exact phrase - like in a departmental store.
• Support bots’ incorporation with AI technology will be able to cater support in most obvious problems, hence cutting down the manual support and team requirements.

Death of language obstacles: This is going to be the peak change in the realm of CRM landscape. Natural Language Processing or NLP, which is commonly known as speech recognition will become more advanced in order to provide an emotional analysis of the speech. It would aid in targeting brand evangelists and dissatisfied customers in no time. In a nutshell, this intelligent CRM too will intent to quantify and examine customer behavior and be able to predict the same. As a result, marketing and sales team would be able to outline the strategies for desired results.

• Manual processing of data has always brought the CRM database in crucial consequences, related to the quality of data and further shackling the customer transactional quality.
• Thus, Intelligent CRM would reduce the requirement of language training to sales force while capturing data in a manner that minimizes impure data input and increase data sanity.
• In order to leverage NLP, speech recognition will aid in sorting and analysing the customer interaction basis the tone of the voice as well as the content of the speech. In the end, it will result in identifying if sales pitches are completed properly.

To sum up, CRM is a direct link of revenue maximization of a company. To support, Gartner predicts that it shall continue to outpace the overall enterprise software development. Moreover, in other ecological unit as well as technologies are likely to impact traditional CRM systems and interaction models (tele compliance, face-to-face). For instance, video calls and ‘Holoportation’ has become the order of the day for the sales team. The new CRM systems with such capabilities will soon emerge to cater a much better experience for both sales agents as well as end customers.

However there is a key role to be played by the training data here, since ML algorithms will depend on the training data to improve accuracy of outcome. The responsibility of feeding accurate training data to train the algorithm to become highly accurate in its inferences will still be a high dependence to make the enhancements in the CRM effective and correct.

Has integrating technology with CRM tools helped in optimizing the pricing decisions? If yes, please explain.

Technologies like predictive analytics, geo-analytics, ML and AI can be used to enhance pricing of a product, basis the customers, market, demographics, purchasing patterns etc. Consequently, this will aid the sales team to adopt “go-to-market” strategies which will align their efforts and investments to target territories with maximum sales potential. As a result, it will also have a direct impact on the business’s margin, income growth which were more than predicted.

For example, a study done by McKinsey & Company validates that 30% of the pricing decisions which companies make every year fail to boost the price that would deliver the greatest margin and revenue growth. With the increase of 1% price translates into 8.7% in operating profits, assuming there is no loss of volume, thus pricing has substantial upside potential for improving profitability.