Everyone has been banging on about retargeting recently.
Publishers were loving the boost in revenue from programmatic advertising, which basically uses up what would otherwise be remnant (very low value) inventory at a premium rate. But now they are a little scared that the furore over third-party data is going to turn this type of programmatic marketing into problematic marketing.
Retailers were loving the way they could hassle the hell out of would-be customers who had left an abandoned basket, and could now be chased around the web by adverts that reminded you of the skinny jeans you almost bought.
And consumers… well. Yes. We hate being spammed. Reminding me once about something I didn’t buy is cool. Maybe. Thinking that 17.2 impressions over the next 1.5 days is going to help, well, it ain’t. Especially when I was just in a moment of hipster weakness, before realising my belly would overhang the jeans in a not-quite-so-Shoreditch fashion. The great unwashed masses (I’m extrapolating from this audience-of-one for this) didn’t like it, but add in a whole load of spice from privacy groups and mainstream news outlets, and the resistance carries more weight than ever before.
What’s not right?
Well a few things. But beyond some of the more discussed issues, the core issue here is around timeliness. Honestly, it’s not often that I go to buy something, don’t buy it, and then decide I need it, because I was reminded. It does happen. But not often. I would categorise this type of marketing into three approaches:
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- Influencing how people decide
- Influencing what people buy
- Influencing when & where people buy
In an backwards analysis, with escalating awesomeness…
Number 3 is retargeting. The decision is pretty much made, and the trader is shouting loudly to call you back to their (virtual) fruit stand. This definitely works. Can piss some people off. But it produces EASILY measurable results. Lots of vendors are playing in this game, including Google Ads and other big boys, as well as interesting specialists like Triggit (Facebook Retargeting) and Chango (search retargeting).
Number 2 is offer recommendation. You have decided to buy something, and now you are choosing between several similar products. There are a few different approaches to this, some completely statistical (eg collaborative filtering – “people like you also liked”) and some built from rules on your unique profile. The value is measurable, and can be considerable. You can take the approach of choosing what people are most likely to buy, or optimise based on order value. The vendors here are across many channels, and range from big-ass systems like Pega’s decision management suite, to in-email providers like Emailvision’s Predictive Intent or Exact Target’s iGoDigital, to on-site providers like Baynote or Certona.
But Number 1… well, yes. I have a special place in my heart for Number 1. It is more complicated. But if you can extend your reach up the sales funnel, before people are too far through their decision process… well, you can later influence them to a product or service that best suits their need (and is in your best interests). Traditionally, this is the arena of brand advertising, PR and the like. Today, we reinvent and these things to become native advertising and content marketing. This is where vendors like idio come in – and others like Sailthru or Rich Relevance or Grapeshot.
The earlier you have insight on a prospective customer, the earlier you can influence and measure their journey. Not only does this give you a MUCH better forward visibility of buying behaviour, but allows you influence that journey earlier. This has a massive impact on business value. In a ZMOT world, companies can often only heavily influence the final 10% of a customer purchase decision; ie when they walk in the store, click on the site, or similar. But if you can get visibility earlier, by talking about the aspirations, lifestyle interests, needs and wants of your target buyer, you can build a process of pre-targeting; predicting the customer journey and therefore helping them solve the problems they need to faster and easier, and obviously whilst buying your product or service.
Some practical examples:
- If a major bank is emailing (ideally in a heavily personalized and relevant way) their customer base about yachts, houses and potential job opportunities in Norwich, the potential of seeing the signals in who is undertaking any of those life events before they occur would allow the bank to engage and lead to a product recommendation. Without pre-targeting, the bank would only know you have moved to Norwich when you have changed your address to the house you bought with a mortgage from one of their competitors.
- If an automotive manufacturer gave its customers all a smartphone application which served personalized event recommendations and news based on their favourite sports teams and pop bands, in order to suggest drivable outings, it would be gathering data on customer taste which would be current, and able to inform sponsorship and advertising opportunities, as well as future customer engagements.
- If a newspaper is trying to drive paid subscriptions by advertising to those who have started reading a few articles for free, it could use the topics of the articles they have already read to recommend an awesome few articles that are behind the paywall. This would provide a really compelling reason to pay now, rather than just pushing everyone a Subscribe Now banner advert. Everyone wins.
If this piques some interest, or you want to chat about how this might work in your situation, just drop us an email to email@example.com, or on Twitter at @idioplatform