Target knows when consumers are about to take a business trip, or when a barbeque might be an idea by examining consumer data and aligning online behaviour with offline activity.
During Advertising Week Europe recently, data was the word on everyone's lips.
Data worked its way into every session, panel and debate in all of its forms: as the disruptor of sectors, as the antidote to flailing marketing efforts, and as the passport to razor-sharp insights.
One thing that became clear was that while brands are tapping into the opportunities their swathes of data present them with, they’re still running into teething problems which prevent them from really maximising those opportunities.
My ears really pricked up at one panel session when James de Souza, head of customer analytics at the Post Office, admitted that there was a particular difficulty around analysing data according to intent - and then once that’s accomplished measuring it effectively.
Intent; that crucial, even magical, period of time when someone is thinking about buying a product or service. It is notoriously difficult for brands to source this moment, pin it and act on it accordingly – to identify and target a person with exactly what they are looking for, before they start looking for it.
De Souza explained this in the context of a person who is thinking about buying a mortgage.
In order for the Post Office to actually provide this person with the right information and support as they embark upon the research stage (and stand a higher chance of being chosen as the mortgage provider), it needs to have some kind of capability in place to pinpoint that moment ahead of time and act on it.
Retailer Target can predict business trips
One brand that has nailed the identification of intent? Target.
The data mining formulas used by the American retail giant are so sophisticated, it knows when consumers are about to take a business trip, or when a barbeque might be an idea, well in advance by examining consumer data and aligning online behaviour with offline activity.
Specific departments in Target stores are working with such precise prediction-models that when consumers buy certain products, signals are then shot through datasets to flag that person might need certain (and even unrelated) products within a certain amount of time.
Needless to say, this is working fantastically from a marketing perspective, and hits the right balance of being helpful rather than intrusive.
The magic of intent
Registered user data creates profiles on real, identifiable people and their devices - cookie-based marketing, though, is based on likelihood - and therefore usually inaccurate
Brands who invest in advanced behavioural patterning are well on the way to unlocking the magic of the intent stage, and approached in the right way, this increases the chances of brand awareness and loyalty tenfold.
But this is no easy feat, and it’s made even more difficult as consumers switch fluidly between their phones, desktops, and tablets throughout the day.
This triggers significant gaps for advertisers who think they have a ‘holistic’ view of their consumers. In reality, they don’t, which makes measuring or acting on customer intent essentially impossible.
Having the data banked just won’t make the cut anymore – it’s now about making sure data is gathered seamlessly in real-time. This will propel brands into the sphere of predictive marketing and, most importantly, allow marketers to deliver helpful and relevant advertising for consumers.
If Melissa from East Croydon researches interest rates on her work computer, local schools on her mobile phone and leisure centres on her tablet at home, those activity flares can be measured and traced back to indicate that she is likely to be thinking about a mortgage. This is then flagged to the Post Office, and so on.
Monitoring and measuring intent can only be done to its most effective degree by leveraging a consumer’s first-party data.
Registered user data creates profiles on real, identifiable people and the devices they use. Also known as ‘people-based marketing’, it has earned its spotlight because it mines in on core, secure and accurate data.
Consider this in contrast to cookie-based marketing, which is based on likelihood and therefore usually inaccurate.
Pinning that magical moment down, and acting on it with a capped approach across all of Melissa’s devices means brands like the Post Office can start telling her the story she wants to read, before she has tried to find it.
The accuracy gauged from the careful data ‘mapping’ of customers’ registered user data means brands can be spot on with their approach – and spot on for the rest of the customer journey too.