Most ‘big data’ marketing is a waste of time, and here’s why
Using big data to look at past trends is not the best way to work out what your customers want, argues Peter Swan of the UNSW Australia Business School in this cross-posting from The Conversation.
A passer-by happens upon a drunk searching for a lost wallet under a streetlight. With nothing in plain sight, the passer-by asks “Where did you drop your wallet?”.
“Over there,” gestures the drunk across the street, “but I’m looking here because this is where the light is.”
We often look for answers in the easiest place and not necessarily where the answer is to be found. As marketing moves from subjective art toward objective, data-driven science, are we seeing the emergence of a streetlight effect?
Are even the very best big-data driven practises guilty of asking the wrong questions of the wrong data?
An interesting perspective on the ‘big data’ phenomenon. Many organisations burn cash to market or optimise their proprietary algorithms or data sets for the purpose of building confidence around their conversion metrics.
The delusion many of us fall under in programmatic marketing is to think that we run ‘physics engines’, based on predictable laws of nature to determine future human behaviour. We build data stacks to the moon in the vein attempt to create an disputable law of consumption for the SUV or baby bottle market, and just when we think we have it, we’re confounded by fast diminishing returns several hours later.
However, without a scalable approach to qualitative research, containing explicit questions about intent or price point (a la Google search), then display programmatic will insist on more data points, not less, to ‘reset’ the clock when diminishing returns set in. That said, we need to be far more discriminating about the data employed, and be prepared to pay for data with high integrity.
Using large, accurate and granular data sets that tell you things about your target audience you did not know before, or worse assumed wrongly, is a good thing. Having that delivered in real-time, or close to? Even better.
And don’t target drunks.
Long read (but related).
Suggests much of the push for “big data” is to have a compelling story to tell investors, regardless of its veracity.
http://www.theatlantic.com/tec.....in/376041/
Decent read.
Marketers have overlooked residual value in their efforts for decades… and mostly based future plans and strategy on campaigns and tactics that didn’t work. Regardless of the maturity and use of Big Data or Technology, leading companies still need ‘thinkers’ to reflect and project what they want/ need as a business and how to validate that against their customer base, regardless of channels, offers, tenure etc.
If it was easy everyone would be doing it.
Kinda reminds me of this emerging need for companies to build ‘Loyalty programs’, when in fact all they want is ‘Loyal behaviour’…
Thanks for the thread Peter.
“practices” not “practises”
As someone who works in data and analytics when it comes to modelling there’s no such thing as big or small data – just data, Big and small data are buzzwords. Maybe it was just me but also I don’t understand Peter’s point. If historical data (big or not) cannot be trusted to predict the future how can small data? Any data point is by its very nature historical.
Search costs definitely can be reduced through “big data” (using Peter’s definition of data sourced from previous customers), ask Amazon and the sales that come as a result of their “recommendations”.
I agree Alex. I don’t really understand the point that’s being driven at here. Clearly there are things that can be learnt from past data (toy sales shoot up in the lead up to Christmas, there’s an increase in people going on holidays in January) that will help marketers plan and get ahead of the curve.
I’ve always hated big data as a buzzword (never heard small data, but I’m not going to take that out for dinner either). End of the day it is all just data – yeah, you might need a big database to store it all and sexy new technologies to organise and query it – but in the end you’re just gathering data points and trying to learn from them.
A great article Peter, thank you. We tell our clients that it doesn’t make sense to keep mining the past to predict the future. We tell them that not only is that not wise, it is expensive and takes a long time. Plus, you only know what your customers do with you, not what they are doing after they have left you or your brand. Which is why we tell our clients it is best instead to connect to real-time data with an intention to answer what is happening right now. We’re helping them do this by mapping Australian users on the social web – these are our clients’ prospects and customers, providing vital feedback which can inform marketing and sales programs. This is Social CRM at play – providing a more complete and up to date view of your customers and prospects. With this in mind, we would argue that big data marketing is far from a waste of time – it’s essential. The key to success is leveraging technology to make sense of the social web.
I work client side, I just got a call from bimbo agency. Oh I need visitors, bounce rate, mobile users… *rolls eyes*
You wouldnt know what to do with the data if it hit you between your the hipster glasses..
Don’t ask for metrics please
As a marketing student, I’ve been reading volumes on big data and it’s value so it’s almost refreshing to have another point of view. As Peter suggests, circumstances can change in an instant so regardless of a businesses marketing efforts and data analysis, a situational influence may having the final say in a purchase.
The best predictor of future behavior is past behavior 🙂
The value of any data to marketing is directly proportional to the marketing talent directing it’s use.
Yolo I say