When It Comes to Data, Go Smart Before You Go Big

There is a lot of hype around big data, but integrating a broader range of smart data sources can help achieve revenue goals in a more efficient way.

If you work in marketing, there’s a good chance that you hear or read the words “big data” at least a few times every day. But what does it actually mean? Column after column and conference deck after conference deck confirm that many marketers, agencies, and tech vendors are at a loss to explain what this phrase means and if indeed they need a big data strategy.

So now it’s time to pop the big question: Is big data really the best choice for marketers who are looking to move the revenue needle? Or is it really just a big mess?

The truth is, what data scientists are usually referring to when they use the term is a mass of data generated by an organization that includes both unstructured data and structured data.

Unstructured data is not organized according to a pre-defined model or scheme. Structured data, on the other hand, is data that has already been filed in some kind of system in which it can be referenced according to a defined scheme. The latter category is what, in marketing terms, you might call smart data – the marketing-friendly cousin of big data. And smart marketers are using this type of data to make their ads more personalized and relevant and their ad spend more efficient.

The good news is that today’s marketers have many sources of smart data at their fingertips. In most cases, and through many channels, they have demonstrated the ability to connect with customers in informed and appropriate ways using Smart Data in many parts of their exiting business.

However, digital marketing is one place where there is still a huge opportunity for marketers to tap the full value of their unique data assets. Smart data sources can include anything from customer relationship management (CRM) databases to historical revenue or yield management data. In real-time marketing channels like programmatic display, it can also include real-time data streams about user behaviors or online shop and advertising performance.

When it comes to customer data, just think of all the rich data sources that marketers have available to them today: brick-and-mortar store metrics, loyalty program membership, website activity, email lists and open rates, purchase histories, return rates – the list goes on and on.

Then add to it the yield and revenue management lessons learned from years of doing business: which products can be priced higher, how to scale discounts and sales according to seasonal demand variation, how to increase margin with in-house brands, and more.

The problem is that much of this data is stored and managed in separate silos – customer data has been the purview of marketing while inventory and other business data has had its home elsewhere in the business. The result is that most CRM systems push offers and messages built around specific customer “profiles” or audience segments without regard to other data that might be valuable.

At the same time, revenue management objectives are focused purely on maximizing profit based on controlling inventory, adhering to sales and discount best practices — all without regard for the needs of the holy customer. By intelligently combining smart data to drive powerfully personalized digital marketing, marketers can not only send the optimal offer to each individual based on his or her preferences, history, and desires, but also to do so while promoting customer loyalty and driving lifetime value of that consumer to the business.

So how can they start? When it comes to putting data to work, few channels can do it better than programmatic display, where machine learning reigns supreme and real-time algorithms can help marketers make the right marketing decisions based on both real-time and historical smart data sources.

In practice, it might look something like this:

Anna is searching for a new apartment in Singapore using her go-to online classifieds website. She enters her preferred ZIP code into the search and pokes around, later leaving the site.

CRM data shows that Anna is a loyal user of this website with a high customer lifetime value potential based on the fact that she has used the platform twice to find apartments in the past five years and even sent a recommendation to a friend two years ago.

Real-time on-site behavioral data from her research search and updated profile info shows she’s recently married and now looking to buy rather than rent. Meanwhile, of the flats she has browsed, two were from agencies for which this site has a higher profit margin.

An advanced programmatic display platform would be able to ingest all of these smart data points in order to reach Anna with an ad showing the right product (in this case apartments) at the right moments (those when she has time and attention to invest in shopping for apartment listings online) on the right devices (in this case mobile might be paramount!) and purchased at just the right price (as a high value user the classifieds site would be willing to pay more to reach Anna).

The result? Perfectly personalized programmatic advertising that delights Anna by revealing her dream apartment while helping the classifieds site to increase its margins as well as the efficiency and effectiveness of its advertising.

It may sound like data fairy tale, but it’s already a dream come true for many marketers today.

Take for example the Indonesian online baby story Bilna.com, which found that by segmenting its customers based on CRM data, they could target post-baby-phase customers with other relevant offers from its shop.

This strategy enabled Bilna to focus its display advertising investments on new users and the most relevant existing customers, taking into account historical CRM data to help predict customer lifetime value and adjust bids accordingly.

CRM data made it possible to more accurately personalize the ad creative for each impression won, thereby significantly increasing overall budget efficiency compared to its existing display strategies.

Integrating a broader range of smart data sources can help marketers to design customer-centric marketing that also helps them achieve their revenue goals in a more efficient way. So why not give the big data hype a rest and start marketing the smarter way?

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