De-coupling data from media buying – the pros and cons

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De-coupling data from media buying – the pros and cons
Andrew Darling

Blis_Decoupling_Data

Thanks to the rise of programmatically traded media, Agency Trading Desks (ATD) are able to access a lot of mobile data to help buy more transparently for their clients. But they need to take extra care with location data – it’s different.

It was just a matter of time. The ad-buying efficiencies offered by automated agency trading platforms, combined with shifting consumer device trends, has resulted in the merging of mobile and programmatic in 2015. It’s obvious that programmatic advertising will become the basis of a growing segment of ad trading next year, driven by economies of scale and growing demand from transparency-hungry advertisers. The trend for digital media buying is increasingly moving towards the ATD model.

The rise of programmatic is also leading to a reorganisation of the entire mobile ad industry. More and more buyers and sellers are agreeing to deliver premium, direct-sold campaigns though programmatic pipes. Media agencies are aligning their trading desks closer to the research and insight business of parent agencies in an attempt to offer “real” value to clients. The end result could see the trading desks of today operating more like “technology hubs” – with the right pipes in place to drive optimum media spend on inventory for their clients.

ATDs are driving efforts to collect and use multiple sources of data across different screens in order to improve the ability to track users and increase the accuracy of targeting options via audience profiling. They also want to offer the most cost-effective pricing models they can access from mobile programmatic players.

The flexibility of programmatic, coupled with mobile-specific capabilities like geo-targeting, does create, at first sight, an apparently efficient method in targeting the right audience, at the right time and importantly, at the right cost.

So far, so good.

Marketers are following consumers’ mobile behaviours and that means delivering messages where the target audiences are looking i.e. the palm of their hands. Marketers can now merge and extend desktop insights by combining them with mobile-specific data sets like location, device, and content behaviour.

However, from a location data point of view, we know that ad messaging receives the highest attention, based not just on the platform delivered to, but also on an understanding of the actual physical location, both real-time and historical, the device user is in. Take a look at some Blis research we carried out on this subject earlier this year.

Demand-side platforms like Blis incorporate first party location data, second party behavioural, demographic and device data, and data from third parties that can better enrich user targeting.

Complex algorithms piece this data together and create a useable audience profile. Using data in this way significantly increases the transparency, efficiency and performance of a marketer’s ad spend by ensuring the delivery of relevant ads thereby increasing brand awareness, engagement and ultimately sales. Good news for us all!

As expected, the last 12 months have been a continuous evolution in programmatic. The thirst for knowledge and understanding from both agency and clients remains strong. Yet programmatic is still very much in its younger years and it’s only through open collaboration, de-coupling of data, and working in partnerships, that the greater opportunities will become apparent in 2016 and beyond.

Blis supports this collaborative approach and has made the best proximity location data available to be purchased by ATDs. We’ve de-coupled our data from media buying and now offer clients a Managed Service (Media and Data), as well as a Self-Serve Platform (Media and Data or Data only).

However, while programmatic may remove some of the middlemen from media buying, it’s by no means a replacement for entire teams.

It’s about workflow automation, not intelligence automation.

ATDs need to be aware that using location data to buy media programmatically is a complex process and one that requires careful consideration of the pros and cons.

We’ve looked at the pros above. Now let’s dig a little deeper into the campaign performance level.

Successful, intelligent, location-based campaigns consist of three main elements: Audience Targeting, Optimisation and Reporting.

Targeting

Taking the data out of our platform will remove all users who are in the vicinity of Places of Interest (POI). In other words, no proximity. When device ID data is purchased like this it risks becoming stale over a comparatively short time period because the user will have moved on by the time the ATD uses it to buy media.

Secondly, it will also remove device/audience reach because the data will only have device ID’s up until the data moves out of our platform to the ATD. We can overcome this obstacle easily though by refreshing the data sent to ATDs, but it is potentially an issue they will face from other third party data providers as device IDs are passed on in various formats and match rates can vary considerably. The more devices, the better the reach and performance of a campaign.

Optimisation

The Blis platform is a “location-geared platform”. The crucial element of this is using current and historic location information to optimise campaigns. For example, if we are looking for ‘primary grocery shoppers’, our platform may establish that the best performing devices are those belonging to users who also live in affluent areas. Our platform has this residential IP device data and will therefore optimise to these devices, reducing wastage and maximising campaign objectives.

Taking the data without the other historic data we already have on that device, and putting it on a more rudimental DSP, simply will not have the location optimisation algorithms, or the data to run the campaign as effectively as we can as a managed service.

Reporting

Our platform also tracks footfall – both before and after an ad is served – to determine what, if any, changes occur in consumer location behaviour during and after the campaign. We also report on the optimisation carried out by our platform around best performing locations, time of day etc. Taking the data out of our platform and into a vanilla DSP loses all of this.

Blis acknowledges that the current prevailing wind in the programmatic marketplace means ATDs want to be able to buy all kinds of data de-coupled from managed media buying. And we are facilitating this.

However, if the objective is a successful end-to-end campaign journey with optimised targeting, scale and reach, then taking location data out of our platform by itself may be detrimental to that objective across the board. On top of that we have a market-leading DSP connected to a bidder that does all of the above intuitively.

Blis has been doing this for years and we understand how location behaviour determines user context which creates audience insights. Think location is easy? Think again!

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Andrew Darling is Communications Director at Blis. He is responsible for Blis’ global communications and PR activities, as well as marketing operations in APAC. Andrew is a seasoned tech marketing and communications expert, Chair of the IAB SG Mobile Committee and former Telecoms, Media and Technology journalist.
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Shopper marketers’ biggest challenge is to connect their online campaigns to in-store results. RSi’s Ansa solution provides the intelligence they need, based on daily, store-level POS-data from the largest US retailers in order to plan, target, and measure the impact of their shopper marketing campaigns. Retail Solutions Inc. has partnered with the leading ad networks in Shopper Marketing, such as Blis, to make Ansa’s automated analytics available for the world’s largest CPG companies and their agencies. To measure and maximize their digital ad campaigns, all they need to do is ask for Ansa inside their next campaign.

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Blis campaigns optimized with Ansa typically identify and heavy up investment around 16% of stores that are trending significantly ahead of the average store during a campaign and identify and decrease investment around 14% of stores that are trending significantly behind the average store, therefore ensuring that your budget is being optimized surrounding stores that are over-performing during a given campaign.

After each Blis campaign, Ansa automatically generates measurement of Featured Item Lift and Halo Item Lift at both the total event and week levels. Results are completed 5 business days after the end of each campaign and allow you to learn quickly and improve continuously, all at an amazingly affordable price.

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Question 6: If there was one piece of content you think every marketer should read, what is it?
(Other than this blog post of course!)

Think with Google and Facebook IQ are two fantastic sources of resources. Articles, trends, case studies, POVs, insights, etc… pretty much everything you need to read to keep you up-to-speed in this very fast-paced environment.

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Mobile devices provide the answer. By revealing where consumers go, mobile location data can tell brands which consumers spend their time browsing similar products at a competitor’s store. Let’s say Target wants to reach out to consumers who usually shop at Walmart. They can use location data to identify—then target—those who frequently visit the competitor yet still live near a Target store.

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Keep Them Interested

What’s the first thing you do when you wake up in the morning? For most of us, it’s look at our phones to turn off our alarms before checking the weather and scrolling through our Twitter feeds. And throughout the day, we continue to stare down into the faces of our mobile devices: checking the news on the train, sending an email between meetings, or watching videos from our living room sofas.

In order to engage consumers on the devices we use day in and day out, advertisers will need to serve ads that make sense for the consumer depending on where they are during the day. To do this, advertisers must first ask the question: What do consumers want to see on their mobile devices and when? Consumers spend a third of their time online watching videos, for instance, but they aren’t going to watch a 30-second video ad while walking down the street.

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Inspire Loyalty

How can brands make sure they retain the new and existing customers they’ve worked so hard to gain? They must first recognize and show appreciation for their most loyal customers.

Most advertisers identify loyal customers by looking at newsletter subscriptions and online purchase histories, but they may be missing other valuable customers who prefer to shop in stores. By identifying devices that frequently visit a brand’s store location, advertisers can make sure they are recognizing—and thanking—all their biggest fans. When an existing customer comes into a store a certain number of times, for example, advertisers can deliver a thank-you message—perhaps offering the loyal customer a generous coupon to redeem in-store.

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Following its decision to buy e-commerce company Jet.com last year, Walmart recently agreed to acquire Bonobos, a retailer with a strong online presence and generous shipping policies. If these moves weren’t sign enough that the physical and digital retail worlds are merging, Amazon’s acquisition of Whole Foods is the ultimate wake-up call.

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Sometimes, targeting consumers when they are walking by a store may be a little too late. A QSR wanting to boost its 10 am breakfast crowd, for instance, may want to target consumers when they wake up around 7a and begin planning their day. Otherwise, the consumer has most likely already made their breakfast choice.

While there is no one-size-fits-all solution for retailers looking to connect with consumers and drive in-store sales, a strong mobile strategy is key. As the digital and physical worlds continue to blend, retailers must harness the insights and capabilities of mobile to reach their unique brand objectives.

Tune in next week to read all about how mobile is fast becoming the extension of a retailer’s store.

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