Fundamentally, we can program ourselves to encourage a specific cue to drive an (increasingly) automated behavior, bringing us to the reward that we’re looking for. For instance, the Indianapolis Colts won the Super Bowl in 2006 because head coach Chuck Pagano trained them through countless drills to look at different cues in order to generate automated behavior that would react in the reward they wanted (e.g. when the defensive linebacker shifts weight to his left heel, run right and you’ll find yourself empty for a catch).

As I read and researched more on the topic, I began to wonder how we – in the advertising industry – could deliver different cues to consumers that would automatically cause them to react (click on ad à shop) towards a desired reward (satisfaction of a purchase). It is my belief that the more relevant an ad message is to consumers’ needs and wants, the more likely the consumer will click on the ad. This initiates the desired shopping behavior all the way to a new reward/purchase.

Over the past few years, we’ve gotten better and better at delivering relevant display advertising to desktop and laptop users through data retargeting and predictive analysis against what online users are searching for in their local neighborhoods. For instance, if user were to search for “Automotive Repair” in “Montreal”, we would inherently know (beyond any doubts of IP addresses) that this was in fact a Montrealer. Secondly, we would know that this is someone who owns a car and who would likely be very open to promotions for nearby garages and potentially for new car purchases. When we first thought about extending our data aggregation and analysis to mobile searches, we hit a wall. As per Google, over 50% of searches that mobile users make on their smartphones result in a purchase in the same hour! So, even if we were to collect the search information of a user for display retargeting over the next month, week or even day – it just wouldn’t be relevant because the consumer will have already made their purchase and would be thinking of the next thing that they need or want.

Instead, to understand how to better deliver relevant mobile advertising to on-the-go and on-the-couch mobile users, we need to better understand what consumers are doing offline that triggers them to turn to their mobile phones in the first place? IBM claims that consumers interact with their phones – on average – 120 times a day… What is the cue that gets them to do this? In order to try and understand consumers’ offline habits, I decided to map out all of the various offline routines. I mean, I’m a pretty interesting person right – if I could figure out all of the places that I go offline, then I could begin to understand when and where I’m using my mobile phone. Well, after a couple of weeks tracking my offline behaviour – a pattern started to emerge… and it wasn’t nearly as interesting as I may have otherwise expected. Other than the rare trip to a shopping mall or shop, I tended to fall into the same behavioural patterns whereby I wake up  – on good mornings, go to the gym, then work. Afterwards, I’d head back home. Then sometimes go to pick up some groceries at Loblaws, go to one of 5 restaurants, spend Friday night at a friend’s and then… Sunday lunch with family. That was it, week in and out.

Turns out, I wasn’t alone. When I ran the survey with a group of 30 volunteers at Mediative, everyone had similar patterns – going to an average of 22 locations in a week and only 6 locations in a day. A sociology professor at Columbia University claims that this is normal. As it turns out, anchors such as work or daycare create routines and – the more anchors that we have – the more routines we fall into. The only people who don’t have routines are those such as prisoners just released from jail who tend to go everywhere and explore everything immediately upon their release. But as soon as they have 1 thing that they have to do in a day – such as drop off their kids at daycare – they too begin to fall into daily routines. Speaking of which, it was interesting to see that Parents amongst my volunteer group also fell into similar routines based on more anchor points. On average, they went to fewer places – 15 on average in a week, 5 in a day – and they tended to have similar anchor points such as daycares, elementary school pickups and hockey rinks or community centers. Single guys, on the other hand, went to far more places – on average 32 a week and 8 a day – with a ton of restaurants and bars in the mix of their routines.

From our various consumer analyses and studies, we’ve come up with 24 different consumer profiles that have similar offline behaviors and routines.  One of our consumer profiles, for instance, expands upon our “Parents” research to filter down specifically to Pregnant & New Moms. Here, we recognized that these consumers over-indexed at Pediatrician Offices, Pre-Natal Classes, Baby Furniture Shops and Vitamin Shops. This isn’t to say that these are the only consumers who were going to these locations … but – more often than not – they were in this consumer group. As such, to reach this consumer group, we need to deliver mobile advertising to the webpages and websites that consumers look at when in these locations (which we are now doing after detailed lat-long mapping and purchases in multiple ad exchanges). We’ve seen success with over 100 advertisers across multiple industries, from restaurants to computer manufacturers and from big-box retailers to car repair centers (we generated 1% CTR vs. the industry benchmark of 0.19%).

Across the advertising industry – as we continue to play in the sphere of “Big Data” and all of the power of targeting that it brings – I encourage you to think about what data you need in order to drive the right cues to enact automatic behaviors from your clientele.  Of most importance though, in working with data and building digital campaigns, is to keep the consumer – your end-user – at the core of every strategy and every marketing message that is built. On knowing you target consumers’ offline profile and building strategy against this, you’re setting your digital initiatives up for success.


About the Author
Mediative is one of North America’s largest integrated advertising and digital marketing companies, specializing in maximizing the online presence of some of the world’s most respected brands. Mediative has been awarded the #1 Best Enterprise SEO Company in Canada by TopSEOs. Mediative’s best-in-class digital media strategists and experts serve national agencies and advertisers through its two divisions: YPG Ad Network and Mediative Performance. Mediative covers all print, search, display and social networks to drive performance marketing for clients across the entire buying cycle, from brand awareness to lead generation and sales. The company also integrates data, media networks and technology to help advertisers, publishers and retailers connect with audiences. Mediative has over 150 employees across four Canadian offices: Montreal, Toronto, Kelowna and Vancouver. Mediative is a division of Yellow Pages Group (TSX: YLO). For more information, www.mediative.com