A really well written story in Techcrunch today, which relates the ever increasing difficulty of getting a message you publish in front of people you know. Well worth a read if you have a spare 5 minutes: http://techcrunch.com/2014/04/03/the-filtered-feed-problem/
The main surprise for me is that if you “Like” a particular vendors Facebook page, the best historical chance (from Feb 2012) of seeing one individual post from them was around 1 in 6 – 16%. With an increase in potential traffic to go into your personal news feed, it is (in March 2014) now down to 1 in 15 – 6.51%. So, businesses are facing the same challenges to that of the Advertising industry in general, even on these new platforms.
Despite the sheer amount of signal data available to them, even folks like Facebook (and I guess the same is true of Google, Twitter, LinkedIn, Pinterest, etc) have a big challenge to separate what we value seeing, and what we skip by. Even why we look at these social media sites can be interpreted in many different ways from the get go. One of my ex-work colleagues, at a s Senior Management program at Harvard, had a professor saying that males were on Facebook for the eye candy, and females to one-plus their looks and social life among their social circle (and had a habit of publishing less flattering pictures of other women in the same!).
The challenge of these sites is one of the few true need for “big data” analyses that isn’t just IT industry hype to sell more kit. Their own future depends on getting a rich vein of signals from users they act as a content platform for, while feeding paid content into the stream that advertisers are willing to subvert in their favo(u)r – which is a centuries old pursuit and nothing remarkable, nor new.
Over the past few weeks, i’ve increased the number of times per week I go out for a walk with my wife. This week, Google Now on my Nexus 5 flashed this up:
So, it knows i’m walking, and how far! I guess this isn’t unusual. I know that the complete stock of photographs people upload also contain location data (deduced from GPS or the SSID of Wireless routers close by), date/time and readily admit the make and model of the device that it was taken on. And if you have a professional DSLR camera, often with the serial number of the camera and lens on board (hence some organisations offering to trace stolen cameras by looking at the EXIF data in uploaded photographs).
Individually identifiable data like that is not inserted by any of the popular mobile phones (to the best of my knowledge), and besides, most social media sites strip the EXIF data out of pictures they display publicly anyway. You’d need a warrant to request a search of that sort of data from the social media company, case by case. That said, Facebook and their ilk do have access to the data, and also a fair guess at your social circle given who gets tagged in your pictures!
Traditional media will instead trot out statistics on OTS (aka “Opportunities to see” an advert) and be able to supply some basic demographics – gleaned from subscriptions and competition entries – to work out the typical demographics of their audience you can pay to address. Getting “likely purchase intent” signals is much, much more difficult.
When doing advertising for Demon Internet, we used to ask the person calling up for a trial CD some basic questions about where they’d seen the advert that led them to contact us. Knowing the media used, and it’s placement cost, we could in time measure the cost per customer acquired and work to keep that as low as possible. We routinely shared that data every week with our external media buyers, who used the data as part of their advertising space buying negotiation patter, and could relate back which positions and advert sizes in each publication pulled the best response.
The main gotcha is that if you ask, you may not get an accurate answer from the customer, or you can be undone by your own staff misattributing the call. We noticed this when we were planning to do a small trial some TV advertising, so had “TV” put on the response systems menu – as it happens, it appeared as the first option on the list. We were somewhat bemused after a week that TV was our best source of new customers – but before any of our ads had been aired. So, a little nudge to our phone staff to please be more accurate, while we changed every ad, for each different media title we used, to different 0800 numbers – and could hence take the response readings off the switch, cutting out the question and generally making the initial customer experience a bit more friction free.
With that, our cost per acquired customer stayed around the £20 each mark, and cost per long term retained customer kept at around £30 (we found, along the way, some publications had high response rates, but high churn rates to go with them).
The best response rates of all were getting the Royal Mail franking machines to cancel stamps on half of all stamped letters in the UK for two two-week periods – which came out at £7 per acquired customer; a great result for Michelle Laufer, who followed up when she noticed letters arriving at home cancelled with “Have a Break, Have a Kit Kat”. Unfortunately, the Royal Mail stopped allowing ads to be done in this way, probably in the knowledge that seeing “Demon Internet” on letters resulted in a few complaints from people and places with a nervous disposition (one Mental Hospital as a case in point).
The main challenge for people carrying a Marketing job title these days is to be relentless on their testing, so they can measure – with whatever signals they can collect – what works, what doesn’t and what (from two alternative different treatments) pulls better. Unfortunately, many such departments are littered with people with no wherewithal beyond “please get this mailer out”. Poorest of Amateur behaviour, and wasting money unnecessarily for their shareholders.
As in most walks in life, those that try slightly harder get a much greater proportion of the resulting spoils for their organisation. And that is why seminal books like “Commonsense Direct and Digital Marketing“, and indeed folks like Google, Facebook et al, are anal about the thoroughness of testing everything they do.