In Brave New World Aldous Huxley wrote of a world of people segmented into specific groups with predictable & fixed behaviours. Without wishing to scaremonger or sensationalise too much, we now live in a world of ‘Millennials’, ‘Baby Boomers’, ‘Generations Xs & Zs’. Whilst I wouldn’t suggest we totally pigeon-hole people, these terms certainly become a lazy-thinking marketing shorthand which we can all be prone to from time-to-time; & where we attach certain behaviours & attributes to particular groups of people regardless of their individuality.

To take the Brave New World analogy a little further, in our brave new(ish) world of digital & social media, algorithms feed us content that reinforce our point of view on many matters, potentially conditioning our future thinking & reactions. Unlike the characters in Huxley’s book though, we’re lucky we already have the freedom not to look, can contextualise with our own experiences, or just plain sign out, log-off & turn-off!


In our brave new marketing world the likes of Keith Weed, Global CMO at Unilever summarises the challenges we face: “In a mobile first world commerce is no longer about buying. It’s also about browsing, researching, convenience, utility, experience, receiving, rating & even entertainment 24/7Furthermore, there also seems an increasingly vociferous debate between ‘purpose & profit’ for companies, their brands, services & products. Some companies may be considered by people as ‘goodies’, others as ‘baddies’ – I expect you’re thinking of your own personal choices right now. Sometimes though, you have to question how much purpose does an everyday pharma, grocery or any other FMCG brand or retailer warrant, given the limited interest & thinking time a shopper or consumer gives to many of these kinds of categories. But perhaps this is a debate for another day.


For despite all these aspects that make up part of our brave new world, the measures which ultimately dictate corporate & personal success are not so brave & new, in fact they’re rather old world – sales, YoY growth, market share, profit, ROI & share price.

From a selling & marketing point of view, these old world measures don’t seem to take into account how the neat, linear sales funnel of yesteryear has become a confused, meandering mess as shoppers & consumers have numerous different ways of buying stuff off & on-line at any time. Nor do they take into account the almost infinite number of ways of people influencing or being influenced in their purchasing decisions.

Strangely, & yet again, despite all this, as with the measures of corporate success, the ones we use as marketers haven’t changed much either.  Like in the old days, we tend to fixate on numbers of eyeballs seeing our activities, how often they see them; hoping by doing this we might provoke some changes in peoples’ recall, sentiment or consideration for our brands. We still don’t seem to think too much about the incremental sales we might be generating. Much expertise & effort has gone into the techniques for targeting & measuring eyeballs in our digital world & it may have become far more sophisticated; but the same old short-comings are there when it comes to attributing a sale outside of an eCommerce site.

When we do look at attributing traditional & digital activities to sale (whether this occurs off or on-line), on the whole we use the kinds of modelling techniques that worked when media was much more mass & the way we shopped was much more habitual; expecting them still to work when the opposite is now true.


Ironically, we frequently talk about the connected consumer, but as commercial & marketing people, it feels like we’re becoming increasingly disconnected. Whether we work in ‘trade’ or ‘brand’, ‘shopper’ or ‘consumer, ‘digital’ or ‘traditional’ the numbers of isolated silos we put ourselves in seems to be growing. So when it comes to deploying marketing activities, whether in store, on pack, out of store, off or on-line, we end up comparing apples with pears when it comes to performance. It makes our lives very difficult when we try to demonstrate the effectiveness of our work to all our stakeholders.

It’s been said many times before, but we really do need to find a way to join everything up. The shopper & consumer does it, so why can’t we in or professional lives? Far be it for me to go into how we structure our companies & industries, but the starting point is surely some kind of unifying currency that at least enables us to compare like-with-like.

At this point I have a confession to make. Having spent more years than I care to remember planning & buying media for large agency networks, & then a few more years with major data science consultancies, I too was trapped by the consumer/brand language of the former; and the shopper/trade language of the latter. No matter how much I tried, I failed to join up the two sides either structurally within either of these two kinds of businesses, or corporately across them. It meant while working with some of the leading manufacturers & retailers across the world, I was unable to give them the joined-up view their commercial & marketing worlds deserved.


But perhaps the most important thing I learned working firstly with communication & media audience data, research panels; then later, off & on-line sales data along with loyalty scheme data, was there is something that can join everything up. A common currency that can marry traditional & digital worlds with the measures that business success has always been built on. This common currency seems blindingly obvious when you think about it, but is so rarely used beyond very specific ‘trade’ and shopper marketing discussions & plans. This currency is based on how people shop & the KPIs that support it.  With the right methodologies, which I’ll touch on shortly, it works across all retail & media channels, off & on-line.

It’s a brave new world when we start targeting, planning & evaluating marketing communication in all its forms by its impact on incremental sales & ROI; ability to drive brand trial & repeat purchase; increases in weight & frequency of purchase; how it changes peoples’ share of requirement; encourages brand switching, moves people from own label to brand, increases or decreases their price sensitivities.

I can’t help but feel that being able to see how your brand’s ‘purpose’ increases your share of wallet or requirement within a category is a much better measure of brand loyalty & equity than anything else. It really does measure the lifetime value of a shopper or consumer.


The key to achieving this seeming nirvana is the ability to collide together the varied data sets involved & create meaningful & actionable insights. It’s why I set up CollidaScope (semi-pun intended) to overcome the frustrations I found in such a discombobulated world.

At CollidaScope we’ve developed methodologies where we bring together what people do through their off & on-line shopping behaviours with the influences of why they’re doing it. In this way we can look at both short term sales effects of campaigns in conjunction with longer term changes to shopping behaviours; the impact of competitors & their activities on clients’ brands & category behaviours. Importantly we can detect the influence of changes in sentiment or awareness on sales, even if though sales may occur at a later date.

Furthermore, since the data, like life, is continuous, we can track effects & help clients course-correct their activities to meet the KPIs that best suit their short & longer-term objectives.

So you might find that good old TV & out of home along with retail media gets people to trial a brand; on-pack & mobile gets them to spend stretch or X-buy; & that you don’t use social media unless you’re trying to get your existing shoppers & consumers to engage with some NPD.

Using our methodologies, means the targeting possibilities are almost endless, & as the media platforms in & out of store become technically more & more sophisticated, the opportunities to implement this approach are growing rapidly across peoples’ varied shopping journeys & communication touchpoints.

While this is not the place to go into depth on CollidaScope’s proprietary methodologies, to make this all happen we use advanced analytics to establish peoples’ degrees of exposure & interaction with marketing activities & isolate which messages, mixes, weights & laydowns of campaigns have particular effects on behaviours. For our clients we operate in a number of ways. Looking back at past activities to inform future strategies; using predictive analytics & the very overused & relatively abstract term AI to scenario plan future activities; & critically our proprietary software, CollidaTrak™ tracks performance against the KPIs that suit objectives, enabling campaigns to be course-corrected to meet them.

This can all be done at single or multiple promotions, media channel & activity-type levels, establishing what works best both singly & in combination. KPIs that support this can range from ROI to halo effects on the brand & category (& vice versa with competitive activities); the impact of awareness, recall, sentiment & advocacy on sales (even if this occurs 2-3 months down the line); along with the shopping behaviours that drive these sales increases –  all to inform your future strategies & plans.


Ultimately the proof of the pudding in all this is in the eating. Applying these techniques to our clients’ businesses has provided them with some great successes. In the healthcare category we increased the incremental sales generated by their brand’s campaigns 4-fold. We did it by working out what was the best performing SKUs to promote in their TV ads to produce a halo sales effect for the whole brand; changing messaging from one of fact-based health to the softer end benefits of the product’s usuage ; & perhaps most importantly, while as a strategy the client had been focusing on winning share of voice, they were losing at shelf, so in-store was where they needed to focus. We found their marketing had been doing a better job for the competition & category, than the category had been doing for them.

For a skincare brand who were using social media to demonstrate efficacy & provenance, we discovered that the only time there were any changes to shopping behaviour amongst a large minority of social media users, was when posts focused on in store promotions. Furthermore, the value of the shoppers exposed to the social media campaigns over a 52-week period remained unchanged. This finding has fundamentally altered how this client now uses social media.

With another client we helped work out the relationship between their off & on-line shopper marketing by establishing that eCommerce shoppers who also saw traditional in store media spent 26% more off line than those on-line shoppers that did not. It was almost like a reverse show-rooming effect.

You don’t need vast amounts of data to get to these results. Brand & category sales data, preferably by geography & store format often suffices along with eCommerce equivalents. Household level data through retailer loyalty schemes are a plus, but not vital. Communication & media audience data are also required along with competitive activities, none of which is difficult to obtain. The key is to be able to join it all up in a robust & meaningful way.

We know from the work we’ve done that we’re boosting the incremental sales of our clients’ marketing activities by up to 20%. We’re doing this by putting all they do onto a level playing field, enabling us for the first time to compare like-with-like, whether its traditional or digital, in or out of store.

Maybe this is our brave new world.

From the Health & Beauty Awards Seminar, October 2017.

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Posted by Lawrence Janes

My expertise has come from working with some of the world’s leading retailers and brand owners. These include the likes of Carrefour, Kroger, Tesco & Walgreens; Danone, Johnson & Johnson, Nestle, Pepsico, RB & Unilever.

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