How would your CFO measure customer engagement and experience?

Any business in the world today wants customers as "engaged" as they think Apple customers are. In other words, we [the enterprise] will deliver new products and services that our customers will buy at the prices that will afford us Applesque margins. Most businesses want better customer engagement; however, their CFO's focus is that those customers buy from them. If not, what is the point of engaging with a customer?

Today, we are living in a bifurcated world from a 'customer experience' point of view. On the one hand, we want to measure, value and score engagement, as we want to improve it, for obvious reasons. If we cannot measure something in large scale enterprises, then we cannot improve it, so it is not worth the worry, time and cost. On the other, if we focus exclusively on trying to raise engagement 'scores,' we may take our eye off the ball and not sell at the level that our CFO and the financial markets require.

So far, customer engagement is measured using Net Promoter Score, i.e. how likely a person is to recommend to a friend. This is a spot evaluation of engagement, but if you have owned a car brand for 20 years, several cars, in fact, of the same brand; then a recommendation to a friend or not, based on one visit to the service department, may not reflect your overall view of the automotive brand in question.

NPS suffers from a raft of other problematic issues. Its biggest problem being, it’s rarely used to any great effect, for example, to engender up-selling, cross-selling, acquiring new customers, etc. In other words, customer engagement is extremely desirable, but why does it live in its own world- divorced from customer success; or indeed, the financial side of things?

Taking your customer's view into consideration when driving revenue

Surely the real question is — can we measure, value and score engagement; and use these measures, not just to understand and improve engagement; but also, to better sell products and services on a timely basis? Why shouldn't engagement be expressed and valued in dollars and cents? Measuring a customer's commitment to the brand and products in terms of potential future spend?

Enter AI. AI and a data-driven approach affords companies and brands the ability to understand their customer engagement and how to optimize their financial success in a much more profound basis. The bigger the brand, the more products and models, the more interactions on the Internet, the more digitally recorded touchpoints with customers. That's a lot to take in — but the good news is that all these events create digital footprints that can be filtered and sorted into unique individual histories.

All that data, from transaction data to marketing communications to social media, even macroeconomic data, can all be used by AI technology (especially machine learning) to help businesses understand their customers.

The gathering together, in one place, of all the events that are digitally recorded, and could be included in a customer's journey with a vendor, is a new phenomenon that cuts across historic business 'silos', including sales, marketing, support and giant transactional engines in large-scale enterprises, which are usually bucketed under the enterprise resource planning label.

One customer journey per customer is a profound change in information gathering, storage and insights. All the data — including ERP, transactions, telemetry, marketing, surveys, blogs and macroeconomic, the list is endless. Imagination rules. AI can make sense of all of this. Providing deep insights into which customers want to buy what; what inventory should be sold to which customers.

Experts use different terminology for Customer Journey Analytics, but in the end, everyone, including your CFO, now believes that one customer journey cutting across traditional business silos is a total game-changer.

About Cerebri AI

At Cerebri AI, we use state-of-the-art AI to help our clients understand their customers better. Now, you can measure the commitment of your customers across all your brands, predict their needs and present highly relevant  next best action{set}s to create personalized experiences throughout the customer life cycle with reinforcement learning. Contact our VP & GM Consumer Group, James Stojanov at [email protected] to discuss possible use cases for your business today.