If you were to tell a story about your travels to a friend, you would include lots of detail around where you went, how you travelled and what you thought and felt throughout.

If your friend was then to tell a similar story, their preferences would be different. It is this difference between one individual and another that makes it possible for marketers to use data to inform, validate and measure their marketing campaigns. Today, however, much of the data easily available to marketers is unverified.

For example, it’s easy to create a data set for visitors to an airline website who have not undertaken any specific action; non-logged-in consumers who have selected certain flights but not progressed to purchase.

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This information, however, cannot be trusted with the same level of integrity as comparative data where active and personal engagement is noted and associated activities can be tracked. For example, logged-in consumers who have purchased a flight for a given time.

The non-transparent nature of some data also means marketers cannot confidently tie results back to defined marketing objectives and brand engagement measures such as brand loyalty or lifetime customer value. They are instead limited to oversimplified tangible measures such as clicks or views.

Understanding your audience

Addressing this is, in theory, easy as all it requires a marketer to do is be more discerning with their data sets. A more defined – and identifiable – target audience will allow marketers to measure true brand-specific marketing objectives and track these over time.

Unfortunately, that’s not the reality. Using owned first-party data alone is often insufficient as a single individual brand lacks the depth and breadth of information to identify a detailed audience segment.

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It can’t offer a holistic view of consumer purchase patterns, trends or behaviours which comes from consideration of wider associated information such as hotel or car hire choices to complement an original data set around flight choice. The reality is that it usually requires multiple data sets.

A digital data co-op provides a comparative data overview at unprecedented scale by bringing together massive banks of aggregated associated, non-transparent data sources from different but related verticals.

Pooling data in this way reveals cross-industry behaviours and trends which would otherwise be hidden within the silos of individual businesses, giving the marketers who use it enough insight to map their campaigns back to true brand-specific marketing objectives.

Doing this, however, does depend on data integrity being maintained through the implementation of key guidelines across the data co-op.

First, data has to be connected; in other words, not just a large number of standalone data points but a set of associated data points which cumulatively demonstrate behavioural patterns and trends. This is why a specific industry focus is particularly beneficial.

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Second, data must be consistent and associated so it can be easily compared and insights drawn from it. Third, data ownership must be transparent and policy-driven to give brands the control, security and data integrity that they require when sharing customer data. This is reliant on industry-certified security protocols and technology while all being branded in the exact same way.

Customisation vs generalisation

The shift to a verifiable data strategy gives marketers the ability to move away from the more simplistic marketing measures such as click throughs which don’t always link directly to sales and can show poorer return.

Instead they can look at data-driven figures like customer lifetime value, customer loyalty and uplift in actual sales within a group of relevant and targeted consumers.

A 2015 study from Adroit Digital and Forrester reflects exactly that sentiment. Seven in ten of customer insight professionals and digital marketers agreed that implementing a digital data co-op would increase their revenues while three in four reported that this approach would also lower their marketing expenses.

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These figures can be attributed to the fact that data is fully customisable from a data co-op. This means marketers can develop a bespoke data-targeting strategy for each individual campaign which aligns exactly to their target audience.

This will not only offer more valuable insight into the impact of a campaign on brand engagement, but will also enable them to increase the return on each campaign as the target audience they speak to is so much more specific.

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Bringing all this together, there’s no denying that there is long-term gain for marketers who buy into the shared data approach.

The ability to better understand their customers and target their campaigns means they can spend less for a higher return and better demonstrate the results to their business too. What’s the catch? Data must be verified of course.

Sourced by Charles Mi, chief technology officer at ADARA

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