Will AI Revolutionize Customer Success? AI & Surroundings

Shreesha Ramdas is SVP and GM of Strikedeck at Medallia, a Customer Experience Management Company.

It’s hard to turn anywhere these days without someone touting the benefits of artificial intelligence (AI) and machine learning. These technologies are positioned as the answer to seemingly everything and as the technologies that will revolutionize nearly every aspect of business.

At the same time, more organizations increasingly understand the value and importance of carefully monitoring customer health and gleaning insights and feedback that can provide precision and guidance for change; they understand the importance of having an early warning system and illuminating opportunities. Many companies have been expanding their customer success practices and elevating their importance.

AI’s Role In Customer Success

Will AI replace most or all of a customer success team and take over most of the practice? Not likely. Customer success is a relationship-based practice that requires many core capabilities that make us human. These include:

1. Active listening

2. Empathy and advocacy

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3. Cheerleading and encouragement

4. Instruction

5. The ability to deal with abstractions and irregular data

In my experience, none of these capabilities are suited to AI, although that is not to say that AI would not be useful in extending the value of customer success.

Understanding Customer Success Goals And Expectations

The ability to understand what constitutes success from a customer’s point of view is a fundamental necessity. This is often a multi-faceted process that may involve everything from understanding appropriate quantifiable metrics and goals for a customer to meeting emotional requirements, such as creating confidence and trust within the customer’s organization (in upper management or other groups). Different customers may have different issues, concerns and plans, and ascertaining success may take some time and work. The results may not be expected or fit a one-size-fits-all pattern or schema.

Many companies find it difficult to shift their point of view from how the company may view or expect success to what a customer expects. This active listening and open-mindedness takes some training or personality skill. It may also require some digging and persistence for customer success teams to understand both the more apparent and underlying goals of the customer. It also requires organizational freedom — the customer success team should not be tethered to the goals of another group or be saddled with too many transactional responsibilities, such as conducting trainings or resolving support tickets.

Customer success professionals need to be firmly planted with their customers to ensure the company’s goals and objectives are being met, as well as to ensure that they can be champions or advocates for each customer. Sometimes managing the potential dissonance between these two requires exceptional human capabilities. There is a kind of art involved in this process that is far different than a logical equation that would be better suited to AI.

Dissemination Of Customer Information

Another key is being able to properly capture information uncovered by the customer success team and getting it to the right teams in the right way — as well as making it actionable. Having a system of record or a single-pane view that captures customer insight and can associate it with actions is a major advantage. (Full disclosure: my company offers a solution like this, as do others.) It is here that AI might be able to see trends that might not otherwise be apparent. Of course, your success with this step is also contingent upon getting the information in the first place — which, as I already discussed, requires specific human traits and relationships.

AI-Powered Customer Success

AI is good at finding patterns and locating needles in haystacks. It can often make quantitative sense out of voluminous and sometimes puzzling data. It may also suggest corrective measures or next steps based on particular findings and conditions. This may be part of the future of customer success. The reality is, however, that many companies are nowhere near this point. Many are still grappling with the proper model for customer success in their companies. Some do not have a specialized system of record for customer success. Others have inherently limited the function customer success can play by making it captive to another department and its responsibilities. Most companies I’ve worked with do not fully understand that the frame of reference for customer success is the success of the customer — in other words, it is success as the customer defines it. Many do not fully uncover or capture customer insight that can lead to strategic progress.

So, perhaps, AI is a “cart before the horse” when it comes to customer success. It could bring value and even open new frontiers by making insights uncovered by a mature customer success practice more useful. Right now, though, many companies need to progress to the point where AI could be benefiical. This will require maturity and growth, but it is a path many should take to ensure long-term success or even viability.


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