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[4 comments]

Creating a post-demographics media strategy in the age of data-driven marketing

January 16, 2014

Through a special arrangement, presented here for discussion is an excerpt of a current article from the Joel Rubinson on Marketing Research Consulting blog.

In a digital age, marketers have amazing options. Now we can remarket to users who abandon shopping carts, target users who are reading content that reveals relevant interests, and target paid advertising to Facebook users who share the same interests as those who have liked our brand page. Even TV advertising is becoming targeted with 60 MM + households now being addressable. We can even match our customers to website visitors in the Facebook exchange or to Twitter profiles and deliver promoted tweets to our users on their smartphones. Cross-screen marketing V1.0 is here.

We are moving into a post-demographics, data-driven era in which behavior-based media strategies offer recency, relevance, and reinforcement targeting — recency, because it has been proven that ads delivered closer to the upcoming purchase are more impactful; relevance, because the right message to the right consumer at the right time and place is more valuable to the consumer; and reinforcement because most of the consumers who prefer your brand still buy your competitors and as many as half switch away over time.

How does a marketer position itself to succeed with data-driven marketing?

  • Focus on what you hope to achieve. How will data-driven marketing improve marketing efficiency and effectiveness?
  • Develop a big data strategy. What data streams will you leverage for marketing gain? How are they going to be connected? Create the infrastructure to manage your brand audience (customer or website) data, your ad response data, and implement a well-thought out tag management approach.
  • Enumerate the plays in the playbook. What specific behavioral targeting options are available for you to choose from?
  • Equip the organization. Someone needs to own this. They need staff with data science competencies. Create a culture of constant experimentation with a measurement approach that tells you if a campaign is working and if the brand is getting stronger as a result.
  • Change the marketing research mindset. To join the data-driven marketing party, we must harvest insights and metrics from naturally occurring data, think more about prediction than report cards, and realize that marketing in a digital world calls for near real-time response systems that come from sources other than long-form surveys.
  • You cannot control reach, but you can measure it. A behavioral media strategy is too complex to design the percent reach. Yet reach is important so you must measure it as an outcome and then adjust. However, don't just think about consumer reach; consider shopper reach — what percent of those ready to buy are being reached by your brand messages?

 

Discussion Questions:

How does a marketer position itself to succeed with data-driven marketing? What might you add to the suggestions in the article?

While we value unfettered opinion, we urge you to show respect and courtesy for people or companies about whom you comment. Keep in mind that this is a public, professional business discussion. RetailWire reserves the right to edit or refuse the publication of remarks that we deem unsuitable. We may also correct for unintended spelling and grammatical errors.

Instant Poll:

Which is most important to achieving success with data-driven marketing?

Comments:

Two more areas for consideration:

Create an environment and business model that both allows and encourages experimentation to find out what works. Run lots of small tests to show what's impactful sooner rather than later. Then iterate to improve. And do it all over again as things change quickly.

Interactions need to be "in the flow" with the consumer. The messages should be a comfortable part of the consumer's process for acquiring information and developing emotional connections. For example, reviews and recommendations from other buyers - potentially people in their own social networks - are authentic and powerful. So are personalized product suggestions based on an individual's behavior and purchase histories.

It's only advertising if it's not relevant to you personally. Otherwise it's the best suggestion you've had all day.

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Todd Sherman, CMO, Point Inside

Another very pertinent discussion for all of the retailers out there. As time goes by, security for both consumers and individuals will seek and acquire momentum and support from both software developers and legislators. This will create a need for retailers to offer and support more modern and enticing consumer participation plans for the gathering and support of consumer likes, needs and wants information. This is something retail has been struggling with for years with very few lasting breakthroughs.

'gjarnoldjr'

I'd add a perspective from the supplier/CPG marketer side that I think applies equally in retail. I think you will see more emphasis on data driven marketing that fuels better "brand storytelling" where creative melds with direct response in a very structured and purposeful manner. Brands, be they products or retail formats, seem to be getting too hard to differentiate based on their "features." Instead the differentiation happens based on the "experience" and for brands this means building content around how products live in the consumer's lifestyle - best served based on data and analytics both in the pre-planning and targeting phases and post-execution analysis.

The same should hold in retail where the "right message" will need to enhance the shopper's experience so that it's memorable and creates a measure of loyalty. A coupon or discount offer based on prior purchase history probably won't suffice.

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Gib Bassett, Global Program Director for Consumer Goods, Teradata Corp.

A data-driven strategy must work across media. This involves:

  • Attribution models. Understanding first view, first click and last click - and measuring the value of each - yields better spend decisions. Match back data can connect offline campaigns. Attribution is different than optimization.
  • Building a data set. Lists, email newsletters, even daily deals add prospective repeat customers to the top of the funnel. Joel cites how we can match customers to records in the Facebook exchange or Twitter profiles.
  • Not following a customer across media in a creepy way. Re-targeting can run amok when triggers are set too generically, such as all home page visitors. Much better to target behaviors further along the purchase path.

The number of digital media channels used by prospects and marketers will only continue to grow. Data driven models detect not just the highest ROI buys but also golden combinations.

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Dan Frechtling, Vice President, Global Product Management, hibu, PLC

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