Decisioning and the Future of Experience

“The answer is out there, Neo.” – The Matrix

CMOs love few things more than a debate about effectiveness versus efficiency. But until now most of the debate about effectiveness has focused on external investments: The Long and the Short of It is about advertising and media choice, How Brands Grow about brand and distribution, and most of the media commentary follows similar threads.

But increasingly we’re seeing many CMOs turn the question of effectiveness versus efficiency back onto internal initiatives to get a holistic view of their investments. Of the myriad options, which will really drive effectiveness, which are only efficiency savings and how to best balance short-term bang for buck with long-term impact?

In part it’s a response to “do more with less”, an all-too-familiar refrain for CMOs in the current climate. To find ways to grow without increasing budgets, CMOs are looking at the bigger picture. Like Neo in the matrix, they are looking for a bigger truth hidden in the reality that surrounds them.

Hence the rise of ‘Decisioning’, a key pillar of the modern experience. Decisioning is a broad term which refers to the process of using data to make informed choices about where and why to invest, prioritizing enhancement and optimization choices, as well using data to tailor offers and personalize customer interactions. It’s becoming a big focus as more and more CMOs see experience as a ‘whole system problem’.

In my previous piece in this series, I wrote about how Generative AI technologies in particular are helping to usher in a new era of experiences that are multi-modal, conversational and context aware.

One way of thinking about this change is that we are massively reducing the latency between data and content – the internal ‘bowels’ of a business – and the customer or employee experience at the front end. Data is being used to recalibrate and reconfigure what the customer interacts with in near real-time. To move, as we say, at the speed of experience.

As pressure comes on CMOs to find new routes to growth with less opportunity to simply spend their way to it, there’s a growing sense that the biggest source of untapped potential lies in the data they hold – and how well they can exploit it.

To do this requires modernization at every layer of the stack, from the data itself to the technology platforms, through an AI and automation layer, encompassing the way products and services are designed all the way up to the experience layer, where the interactions happen that make the top-line grow.

Optimizing any part of this system might make it more efficient, but the big gains in effectiveness will come from looking the whole system and making choices about where and why to invest.

The problem with analytics

The phrase ‘data-driven’ has become a mantra for marketers. The obsession with measurability has helped make big strides in data-literacy and given CMOs no shortage of dashboards and metrics.

But there’s a snag. Analytics often frustrates in its ability to answer the big questions. We see data on what’s working and optimise each part of the system, but the whole system doesn’t get more effective.

Decisioning can be characterized as being data-inspired or informed, rather than data-driven. It is moving from a mindset of What (“what are we going to build next?”) to Why (“why is this initiative the right investment to move us towards our goals?”). Using data to help us answer the bigger questions.

Decisioning is about taking a bird’s-eye view of all experience investments across all channels. We look at all engagement points in their totality and assess their impact on business outcomes. Not only how channels perform collectively, but how the system can be enhanced and optimized. By looking at the whole system not just its component parts, we see the data in context, allowing us to build better investment strategies.

We’ve recently been working with a large US utility company, for example, where we’ve used their data to tie customer engagements to business outcomes, giving us a model to prioritize investment choices, based on their prospectives outcomes.

Decisioning sits upstream of the traditional investments in customer and employee experience. It is about operating models, investment strategies, the domain of digital twins and data-informed product design.

But it is critical to unlocking the latent value of data and gives CMOs a small chance of squaring the circle of tightening budgets and growing demands for growth.

Here are three questions to ask yourself about your Decisioning maturity:

1. How well are you using data to drive strategic decisioning amongst rapidly evolving experience landscape?

2. How well are you responding to customers’ growing expectations for speed to value in their engagements with brands?

3. How well are you able to model and assess investments in experience for both efficiency and their effectiveness in delivering business outcomes?