How Time Inc.’s Media Agency Is Updating Its Use Of Location Targeting
"Location-based targeting is in our DNA going back almost 50 years," says Matthew Fanelli, SVP of Digital for Time Inc.'s MNI Targeted Media.
Like all legacy publishers, Time Inc. continues to face daunting challenges to its traditional advertising and subscription/distribution models.
One way the storied publisher has been dealing with the “digital transformation” of the last decade-plus is to cut staffers to fit the new dictates of running online and offline magazines, as detailed in several reports like WWD‘s news that between 50-to-75 staffers would be cut on Thursday.
But staff reductions, while certainly cause for attention, is one painful part of its efforts to adjustment to a different world. The other part is the biggest challenge: developing its in-house marketing and advertising capabilities so that its major titles’ sales staffers can show that aligning with major publishing still has meaning for advertisers and consumers.
We talked about the way Time Inc. is updating its marketing offerings with Matthew Fanelli, SVP of Digital, MNI Targeted Media.
MNI has been around since 1964. The unit has since served as Time Inc.’s integrated marketing firm way before that term, which essentially means an in-house media buying and planning agency, was invented. Fanelli offered a rundown of some of the wider digital marketing issues the unit is tackling as well as how it is continuing to refine its strategy to both differentiate itself and meet the needs of its parent company.
GeoMarketing: We talk a lot about “location as the new cookie.” How does location data fit into MNI’s targeting and analytics?
Matthew Fanelli: Location-based targeting is inherent in what we bring to a large percentage of our plans. We not only utilize the best-in-class location-based providers but, through our own proprietary Omnipoint Data Warehouse, we collect location-based information as a data metric in predicting campaign success.
Location-based targeting is in our DNA going back almost 50 years. We not only reach your audience, we reach them at the right moment in time, in the right place and when they’re in the right mindset to complete a pre-determined desired action.
How does MNI use location data to drive discovery for offline, brick-and-mortar visits and sales?
We look at geo-behavioral actions as a prediction model based on location of the consumer. This helps to look at in-store action, which results in visits and sales. Reaching consumers in the right location, at the right time, directly drives in store visits and sales. The challenge is in the attribution and how it is being accounted.
Social media marketing is inextricably linked with mobile and location analytics. How do you view the value of new tool like Snapchat’s Snap Map and Facebook Attribution for helping to deliver store visits. Is there any worry about the age-old online issue of “last click attribution,” which ignores all the touchpoints that led to a customer conversion?
The enhanced Facebook and Snapchat tactics will help improve the data behind the drivers to attribution, as the value and benefit of social platforms continue to proliferate. The age-old issue of last-click attribution continues today, and will probably continue into the future. The difference to me is, “What I am doing that merely captures an existing demand (search) versus what I am doing that inspires a demand (display, video, social)?”
The idea of “attribution,” the ablility to tell if an ad actually drove a brick-and-mortar visit, is a big focus of brands these days. How do you view the state of attribution metrics that is currently available to brick-and-mortar brands?
The biggest challenges that brick-and-mortar locations face when looking at what is available to them is really twofold: 1) Limitations of in-store POS (point-of-sale) systems that lack the tech stack to capture what drove the visit and ultimately the sale, and 2) Basing attribution solely off a panel-based study.
Is the use case mostly for what Google calls “micro-moments” – those immediate impulse purchases where someone is looking for a restaurant or apparel retailer near them right now? Or is it mostly about looking for ways to incorporate predictive analytics?
I believe it is both. Capturing someone at the right time in the right location is priceless. This is the Waze example: I am driving down the highway at noon and I get a message to stop at the next rest area for a slice of pizza. This is an impulse and it works. These tactics will also be used to predict what consumers will potentially do in certain locations based off past experiences.
Companies like GroundTruth and Retale have been working with Placed to verify pay-per-visit ad formats. How scalable and meaningful is this kind of ad format in terms of solving the mysteries regarding online ads and brick-and-mortar attribution?
Capturing any level of data is a good thing. Over time, this could be scalable and really provide meaningful information. The challenge is that it is panel-based, relying on what some might consider a small group. There is still the factor of the educated guess.
What impact will voice-activated digital assistants from Alexa to Siri to Okay Google, have on advertising for brick-and-mortar businesses?
Over time, the adoption of virtual assistants (VAs) may hurt brick-and-mortar locations. We see it happening more and more each day, with more efficient and potentially less expensive ways to purchase everyday products. The opportunity for brick-and-mortars is to use VAs for exclusive in-store items and special offers. They also retain the opportunity to bolster their online sales by utilizing VAs.
Does MNI have any initiatives or recent success stories it can briefly highlight in terms of driving traffic for a brick-and-mortar brand?
Two that come to mind are accounts that we have worked on recently. One is a Quick Serve Restaurant where, based on store location, consumer proximity and time of day, we delivered specific messaging. This program resulted in increasing sales by 10 percent over a 30-day period.
The other client is a shoe retailer. We used some standard digital tactics targeting locations, as well as advanced geofencing. Throughout the campaign, we tracked store lift and saw store visitor growth of 55 percent.