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Enabling Marketers to Do More with Less Using Data-Driven Ad Targeting

Senior Content Marketing Manager, Communications Sector, IBM Analytics

Targeted advertising is one of those practices that is most certainly “easier said than done.”

In fact, it’s also easier said than understood.

Because all too often, CMOs underestimate its importance in the advertising value chain and, worse, consumers think it’s an invasive breech of privacy that lies somewhere between “Big Brother” and “Minority Report.”

The truth is far less dramatic.

Nevertheless, sophisticated ad targeting creates a win-win situation for both advertisers and consumers when the effective use of highly relevant messages and offers become personalized for the individual. In the following brief video, Krishnan Parasuraman and I explore this topic and discuss the common misconceptions and concepts surrounding big data-driven targeted advertising:

As you can imagine, the challenge for effective ad targeting is having the ability to look beyond the last click or the most recent search to provide an experience that covers a consumer’s entire purchasing journey.

Why? Because the last step we took is not necessarily representative of the entire journey we are on.

When advertisers and marketers start focusing on all of the available data that can be gathered at each touch-point in that journey – including online clicks, offline sales, searches, reviews, app profiles, mobile data and much, much more – they can finally create a realistic picture of their “targets” and provide a far more relevant experience.

Unfortunately, marketers tend to have difficulty locating, accessing and collecting multi-channel purchase data, so they can quickly analyze it in a way that adds value in this critical process. What we’re seeing is that marketers need to overlay offline transaction data with all of these other online data types – including data from various third-party sources – to gain deep, actionable insights and improve campaign ROI.

And they need to do it at lightning speeds.

There is no doubt that Datalogix® is a leader in this space. They are indisputable pros at connecting digital media with offline purchasing data in order to deeply understand the entire “journey” a consumer is on at any given time.

Currently, Datalogix helps over half of the top 100 consumer marketers increase the effectiveness and measurability of their advertising. Their DLX Platform®, encompassing over $1 trillion in consumer spending, powers campaigns for more than 75% of online media companies. As you can read in our case study, Datalogix uses their big data intelligence in two ways. They create hyper-specific segments and then syndicate them through their channel partners, which include ad networks, DMPs, DSPs and trading desks. In addition, Datalogix built their own ad network to offer marketers integrated media programs, leveraging their own offline CRM databases.

What’s the secret to their success? Scalability.

Late last year, I attended the AppNexus Summit in NYC and scalability was a hot topic throughout the day. The team at AppNexus, a media partner to Datalogix, talked at length about the need to invest ahead of scale so that marketers can proactively make the most of their data as it grows, as opposed to letting it get out of control and either be siloed or ignored.

This is exactly what industry leaders like Datalogix do: they invest ahead of scale.

As their customers and campaigns grew, Datalogix pulled in more and more data every year. And yet, they had the scalable infrastructure in place to effortlessly support this growth so they can continually provide optimized ad targeting, testing, measurement and ROI.

It all starts with optimization and scalability.

If you’re a marketer or advertiser and these words aren’t being tossed around the office as much if not more than the words “big data,” you’re missing something important.

Click here to watch the video