I received an email, out of the blue from American Express. “Advance access to Justin Bieber tickets” the subject header said. It got my attention.
Now, to be clear, I’m not a Belieber, but I happen to live with a few people who are. My home is far too frequently flooded with what I can only categorise as unwanted noise; “Eeny, meeny, miny, mo lover” indeed.
In fact, it can become so annoying that I have to turn to Twitter to vent my frustration, as my daughters tend not to listen to me…they’re listening to Justin.
But quite clearly, American Express was listening to me, and there’s the big data link. I’m on the American Express’s email database, but don’t often receive emails. I haven’t used my card for years, they know this too.
They also have other information about me (name, age, occupation, where I live etc.) and they also have the ability to listen to my social ramblings. Putting all this together, they can socially profile me and match my information to their CRM data. Yet, they don’t bombard me with advertising, they send me a timely and well constructed email about Bieber.
So what else could I do? I reactivated my Amex card, bought tickets, became a hero….for at least five seconds. Imho, it was a very good blend of targeting and enrichment all in one.
Now take another example, but let’s keep this one hypothetical.
A business is structured with a department solely focused on customer acquisitions. They look at the CRM data of existing customers, and segment this list by monetary value. They extract the data of “high value” customers and, with the help of an agency, enrich this data with socialgraph profile matching.
The theory behind this approach is there may be some common interests, demographics, influences, behaviours etc. that could offer fruitful insights about this segment. Theoretically, it makes some sense to use this information to then target “look-a-like” people, who aren’t yet customers, but could be, with advertising.
Based upon the insights gleaned, the business now invest in digital and social media advertising to entice prospective customers over. Will this work?
Here are the potential outcomes:
- It all goes swimmingly well, and consumers and business alike are delighted. Or..
- The business reaches exactly the right people and achieve very high degrees of visibility.
- Through cookie exchanges, they are even presented with ads containing items they have viewed on websites, within social platforms.
- Potentially, these ads follow them wherever they go.
- Click through isn’t great, and cost per clicks are high.
- A performance review takes place, as acquisition is lower than expected, targets are not being met.
- The ad content is revised, the targeting is widened, click-throughs increase, cpc goes down.
- The ultimate result is the original target audience weren’t attracted in the numbers expected.
- This maybe because of the interuptive advertising, they may feel you’ve spammed them.
- They may even feel a bit spooked, due to the information you present back to them about their own online behaviour.
- They may now see your brand in a slightly different light than they did prior to the interuption.
- However, campaign targets are met, due to the revised approach, but the people clicking may no longer be the desired “high value” audience.
In this example, data has been used purely for marketing purposes. Targeting the right people, but with little time spent at understanding how your product or service enriches the lives of existing customers.
If, before this ad campaign, time had been taken to really understand why your product makes these “high value” customer’s lives so much better; why they choose to spend a lot of money with you, would the outcome have been to invest in interruptive advertising? Would it be the right medium to attract new customers? Or would a smarter way manifest itself?
With Facebook and now Twitter, offering the ability for marketers to target people based upon their interests, what people are saying in their updates, who else they follow or like, it requires a lot of thought and planning to decide the best approach. Some have called this functionality “Game changing” as it enables real-time targeting.
However, from a consumer perspective, this means an interruptive social experience, with brands infiltrating their conversations and timelines…if brands choose to advertise. There is no coincidence that many people are leaving Facebook, certain markets may be perceived to have reached their saturation point, but people don’t want to be constantly interupted with marketing messages.
They spend time on Facebook because their friends are there…if their friends start leaving, so will they. Things such as Facebook’s Graph Search (Facebook’s own use of Big Data) will only achieve one thing; people will be very careful on what information they share about themselves, and tighten up their privacy settings; they won’t wish to be stalked, by advertisers or weirdos (deemed to be separate entities).
Businesses, Brands, agencies and marketers need to think really hard on the best use of big data. An understanding of the full consumer journey is a must.
Effort to integrate marketing with product/service design, and understanding why people choose to use your product is now an essential ingredient to success. Understanding this, at the deepest level, will enable you to enrich, entertain and excite people, attracting them to your brand and the people who have already chosen to associate with your brand.
It will also stimulate loyalty and ideally advocacy, which is still the most powerful advertising medium around.
[Image Credits: Taken from Velocity, by Ajaz Ahmed and Stefan Olander]