A few days ago, I met with one of our financial services clients heading into their year end planning meetings. We were meeting to talk about their current developments and what they were hoping to accomplish this quarter. The SVP (we’ll refer him to ‘Jack’) is in charge of Digital Channels, a significant group, crucial to strategy and implementation of digital transformation within the organization, including innovation in payments, customer experience and data insights. They are well on their way to building some great initiatives.

Jack looked at me and said, “We are having some trouble with our analytics team… They are suggesting we invest significant amounts of money building a large database as they say we need to upgrade our investment”.

I inquired whether there was some misalignment. Jack stated they were missing some of the data points that his management team had frequently referenced . The analytics team felt the need to build some infrastructure to warehouse significant amounts of data that would be generated as a result of our new performance.  They insisted on building a roadmap for the next 12 months to define information and parameters that would build definition around their customers.

“We don’t seem to have a problem; our team has a pulse on our customer experience”. Jack felt he had built a good foundation and was aware what needed to be supplemented. This view was different than what the analytics team has suggested.

It occurred to me that the analysts believed that increased infrastructure to house “performance” would help support Digital Channels’ efforts. Ingesting and maintaining the most recent, the most relevant information in a database would allow the analytics team to bring the most value.

The reverse, however, was true. The ability to tap into augmented intelligence meant that information and an activated intelligence framework could enable every person on the team to have access to the most recent and relevant view of the customer – what we coin the Customer Speed of Life. These days it’s not necessary to store this information if it can be unleashed in the process.

Today, insights need to be part of the process, entwined in the decision-making process when it’s most relevant and useful

I immediately shared this with Jack:

This is not that issue. You have made the shift to focus on customer centricity and your team has he ability to manage the dynamic customer journey in and analyze these events concurrently – not just at the end of the process. This information derived from the data itself is the unique strength. By dividing the decision –readiness insights from the operational analytics – the team will provide a more valuable support role and be part of the decisioning engine.

Jack and I went on to discuss the key results areas that now translate from the complex and functional data . This defines the customer-centric culture.

The three Elements Defining a Customer – Centric Culture

  1. Information at customer speed of life. Your customers move at a speed of life They are informed and live in an experience economy. Business must adapt to these rising expectations. This means that processes must change, but this also means that the business must now have access to information that will help modify existing barriers by uncovering blindspots we previously took for granted. By moving analytics and customer identity from the tail end of process and empowering the access to information that can augment into the current process, this puts information directly in the hands of your customer service agents, your sales reps, your analysts – and more importantly, it perpetually places the voice of your customer at every stage of their journey.
  1. Insights in motion (rather than Insights into action) By automating the intelligence and activating dynamic flows using machine learning, this can create individualized customer experience at scale. Traditional one-to-one strategies were misnomers. They conformed to business-define clusters, not individuals. Today, the ability to tap into individualized needs in a way that’s scalable is possible. For the business, this empowers the proactive business narrative that is in step with the customer. Tapping into the ability to answer complex questions that normally occurr in the aftermath, now can occur at the time when it’s most relevant. This allows every conversation to focus on the voice of the customer.
  1. Measuring performance not efficiency. Automation enabled greater scalability and efficiency, but it also left more questions unanswered. The ability to truly measure the effectiveness of our sales and marketing efforts is paramount. Performance means identifying and verifying customers. It also means optimizing based on customer needs, not assumptions of interest (like clicks and traffic). It also means tracking the customer journey from existing personas to our audience and finding those windows of opportunities that can influence customer behavior.

Empowering an organization through data science

What I just experienced with Jack, was the unique crossover between technology innovation and deep learning algorithms that are introduced to translate and improve current business logic. This is the moment of truth when a company can invest in a solution that ultimately empowers their team to produce stronger results, with increased business confidence. They were crafting their own front line advantage with customers, and were ahead of the game.

I have witnessed, far too often, a company tap into a social selling system, for example, that offers the same solution for all its customers. This poses a parity issue but does not address the unique customer experience.

We at verve.ai, proudly see every single one of our clients emerge to be the heroes of their domain. In an age where it’s a good time to be a data scientist, we can enable already intelligent infrastructures with the framework to augment and automate intelligence into existing business frameworks. We have witnessed, time and time again, our clients’ ability to capitalize on this insight, capture the performance criteria and truly tap into the ability to analyze in motion at the customer speed of life.

Jack, and his 120 people organization including analytics teams, were the greatest data scientists I’ve met to date. They quickly understood the power of information and its immediate impact on all levels of the organization.

Data Science for Everyone. It’s not just our tagline, it’s our core belief.

It makes individuals stronger, more productive and more accountable than ever before by instilling confidence rather than process. It gives power to information such as relevant customer micro-moments that can be activated at any customer touch-point. It places the customer at the center naturally. By allowing each person in the organization to have the power of information at their fingertips, the analytics team becomes an enabler to do what is needed, at deeper levels without the pressure of time.

Customer Experience Augmented Intelligence automation supports every team by synthesizing information from disparate and complex data sources, and effectively answering the business questions that will build more confidence in the day to day decisions. What this yields is a stronger performance outcome that can bring more sustainability to the business. These days, the pace of technology and information makes this mission critical.

Your analytics should have the same narrative as your customer experience

When was the last time you were able to answer these questions in 3 seconds or less? How are your different programs contributing to the overall brand perception? Are your influencers sharing the same view point? Can you verify influencer resonance and not just reach? Can you identify your most valuable customers from your social network followers?  Do you know matters to them?

If you can’t let us show you how. We’re just getting started.