Customer Versus Data Centricity


As an integrated marketing and media consultant, I am naturally placing an increasing amount of effort and emphasis on supporting our clients to solve what I contend are three of the greatest challenges facing modern communications today:

1. Marketing Organisations, Strategies & Processes STILL Aren’t Truly & Fully Customer-Centric

Segmentations are rarely fully-operational and largely attitudinal based, fuelling proposition and creative innovation, whilst being under leveraged in terms of adding value to customer relationships on the ground. £Millions have been wasted on segmentations; the graveyard is immense.

Planning remains linear and siloed by channel/budget allocation, rather than being oriented around optimal and cost-effective customer experiences, delivered on their terms.

Emphasis remains on optimising mass communications to reach linear/blended CPAs, which – in many cases - yields increasingly marginal gains.

2. The Information/Data/Digital Age Has Not Improved Marketing Effectiveness

Our obsessive focus on data creates as much complexity, opacity and inefficiency as it solves, if not more. Consumer understanding is still largely lost in the mire of metrics, data sets and models that sit all over the place and haven’t been brought together meaningfully or effectively at a segment level to improve performance.

We all know that consumer data is not insight; yet we still behave in this way.

3. Our Judgement & Focus On What “Works” Is Dangerously Clouded

At varying speeds, the media and marketing industry moves from a first cut of history (e.g. conversions) to subjective understanding at best (e.g. regression/attribution models).

The relentless pursuit of emerging channels, new data and insight has clouded us from securing a mature perspective on what’s factually and objectively true and (therefore) truly valuable. Econometrics was never developed to be a panacea. It was the best we had at the time. At some point, it became one and many have henceforth and unsurprisingly become disillusioned with the practice.

Surely, we have to “fess up” and acknowledge that these models are nothing more than indicative guides of what may have happened in the past, rather than determinants of what we should do in the future.

Moreover, shouldn’t we be trusting our gut more? We certainly need to take a step back more often and ask ourselves whether what we are doing is going to truly benefit the customer experience (ultimately, our end game).

So, What’s The Solution?

Our mission should be to build teams/departments that challenge, reconstruct and network models of data interrogation at a segment (rather than channel/discipline) level, both qualitatively and quantitatively, to fuel greater customer value exchanges, marketing effectiveness and business processes, supported by mass communications.

I’m conscious that I didn’t proffer a solution of what this might look like. I don’t profess to have all of the answers; nor do I presume that there aren’t enlightened marketers out there seeking to answer some if not all of these questions. But, here’s a few areas I’m exploring at segment level today:

Richer Internal & External Data Management & Behavioural Understanding

Source, house, cleanse and fuse a richer single customer view, incorporating LTV data as it becomes available.

Explore interrelated variables with greater precision. For instance, to seek to understand what causal impact clearer communications have on call centre volumes and debt collection, as well as CPAs.

Exploring customer preference and social eCRM in a more meaningful way.

Transition SCV Data Into An Audience Insight Platform

Integrate incremental data inputs such as weather patterns, consumer confidence, Sky IQ, Kantar, IPA Touchpoints and oil prices over time.

Establish a segmented audience panel that can validate hypotheses, both qualitatively and quantitatively – ideally in real time.

Online To Offline Multi-Point Attribution Modelling

Examine the complete journey that converting and non-converting audiences take across all channels, thereby improving targeting.

Model high to low LTV audiences (data permitting).

Blended and single source analysis.

Construct impactor/channel exposure propensity models to better understand what is driving performance/behaviour in real time.

Segment level full marketing mix RO(M)I.

Segment Level Communications Strategies

Bottom-up end-to-end customer communications strategies (in/out of life), to be supported by broader mass communications (rather than the other way around).

Emphasis to be placed on retention, acquisition and total net customer value strategies, more tightly aligned to business performance overall.

Monthly test and learn programmes, segment by segment.

Goal Oriented Causal Forecasting

Segment level decisioning engines, fuelled by sentient systems that scenario plan out of market and course correct in market.

In short, I’m not suggesting for a moment that we ditch the technology, the data and the algorithms. Rather, I’m hoping that we can build colleges/departments around customers to ask different questions from the data and technology to get to a better balance of human understanding, creativity and integration across marketing, operational and transactional communications.