If there’s one takeaway for me from the merger of Heinz and Kraft, it’s that brands are looking to make gains in efficiency and cut unwanted costs in order meet their true business goals and objectives.
Industries across all sectors are feeling the reverberations of this universal streamlining, and advertising is no exception. With the growing ability to track response rates on digital advertising, combined with new ways of collecting mobile and location-based data and the slashing of big advertising budgets based on hyper-targeting, the trend to maximize efficiency continues to grow year after year.
Based on the growth of in-store connectivity through beacons, Wi-Fi and mobile shopping apps, event- and location-based mobile are now vital tactics to consider as a part of the overall marketing-efficiency mix. As retailers continue to collect action-based shopping data on their customers, they’re able to create and refine an even sharper persona of their purchase intender.
This allows brands not only to generate insights regarding shopping habits, but to allow for invaluable foresight into what potential actions consumers may take next based on their already-established persona and data-set.
Imagine the possibilities this type of foresight provides retailers. Here’s a potential scenario illustrating the power of this type of information:
Imagine you’re an electronics retailer looking to clear out all television inventory by the end of the month. One way to get people in the door is to promote a big sale with a national television and print effort to garner potential reach and attention — hoping some percentage of those who see it also happen to be in the market to purchase a television during that month. But that’s an expensive strategy to take. What if you were able to hyper-target only those who were in the market for a new television by using data and mobile targeting capabilities?
Think about the opportunity if you were able to target segments of the population who were of a specific demographic, HHI, location — standard targeting capabilities. What if on top of this data, you were able to create sub-segments of potential purchasers? Those who had visited your online e-commerce site once in the past 30 days, or had a subscription to a cable provider where you run local and national-based advertising, or looked up your location using a search engine on their smartphones within the past seven days or drove past your brick-and-mortar retail location at least five times a week?
Lastly, what if you were able to take conversion data of those who had all of the above segment qualities, and had also purchased a television within the past six months and were able to look for patterns based on the last two "actions" this customer had taken just before making the purchase? Based on those behavioral insights, you would be able to serve mobile search and display relevant advertising to these intenders only, giving them a timely offer to come in and purchase a television for a special price if the offer was redeemed within a certain timeframe.
At the center of this powerful approach rests the ability to track location-specific actions, typically derived from a mobile handset.
With all of this location-based information, a marketer has the ability to create event-based marketing strategies targeting near-term purchasers who are just about to go into the retailer to make a purchase. Imagine how efficient your digital advertising could be with this type of strategy? As brands are becoming more and more responsible for efficiency, looking for ways to analyze and make use of your data becomes even more important.
VentureBeat ran an article in late 2013 saying that one of the hottest jobs in tech that year was data scientist. These sought-after analysts have the ability to look at the massive piles of data that brands and advertisers amass, and decipher trends and meaning in the numbers. They’ve not only been able to generate relevant insights for marketers, but have also been able to collect so much data that, when combined with pattern recognition, they’re able to predict the next move of a potential consumer based on a series of patterns and event-based triggers that would be highly like to take a particular next step.
While the opportunities are growing, there are still challenges to deriving meaning from multiple data points — the most prevalent being mobile location data privacy. Many brands will still require the use of an opt-in and many consumers are wary about brands tracking them through the aisles of their brick-and-mortar locations. Furthermore, cross–device tracking and attribution remains a fixed challenge that doesn’t seem to be progressing anytime soon.
While challenges exist, there are still opportunities to get intelligent about how you track your customers, and how to analyze the information into a meaningful and strategic experience for them. Here are my top suggestions for getting a little smarter about how to gain insight into your intender actions, and their potential actions, that will help you get started in this new world of mobile-location based advertising.
- If you have a retail-based mobile app, ensure the tracking exists within the app in order to geo-locate a user (with an opt-in allow from them) when they are in a specific location.
- Test your way through retail location tracking by installing beacon technology to interact with your native mobile app while shoppers are in-store. Tracking shopper traffic through your aisles is a great way to learn whether there are specific patterns you can take advantage of with specific audience segments.
- Offer up rewards or recognition for those shoppers who opt in and use the mobile app and beacon-response technology in-store as a way to continue to garner insight into their behaviors and habits.
- Test location-based search advertising and begin to build up data on your audiences who conduct local searches, and then take a secondary action like going to your mobile commerce site and convert into a sale.
- Combine your disparate data points into a data management platform so that you can tie all of the points together and begin to take a holistic look into your audiences and look for patterns in the data.
- Work hand-in-hand with a data scientist to analyze data inputs, and generate insights and foresight into your audience behaviors in order to keep an efficient marketing strategy.
Of course, the center of any sound strategy needs to be the audience, and we should all work to ensure that all of this information ladders up to creating enhanced and meaningful experiences for consumers.
Given that there will always be some new technology disrupting the landscape, we need to make sure we never stop working to humanize our relationship with data.
Kayla Green is director of digital strategy at Saatchi & Saatchi Los Angeles.