Do customers really want hyper-personalisation?
Personalisation has been made possible in recent years thanks to the ever-evolving advances in technology. For instance, we have access to tools like http://finecast.com/ which allow super granular targeting on TV; and some agencies claim to be able to build models on consumer passion, these are just two of the marketing technology options which have increased by 3,200% since 2011, it’s no wonder marketers can get distracted by the shiny new technology available.
Hyper-personalisation gives marketers the opportunity to increase our response rates and return on investment for our clients, which is of course a very attractive proposition.
When talking about personalisation it isn’t complete without a mention of GDPR. The new regulations give the control of personal data back to the consumer but have also created a stumbling block for some media channels like direct mail.
As marketers we want the best of both worlds – we want our own data to be secure, but want to access the data we need to make sure our marketing is effective, an issue bought into sharp contrast by the recently shared video of Mark Zuckerberg declining to tell the Senate the name of the hotel he’s staying in. Consumers are ever more aware of how they’re being targeted, but as Mark Ritson states: “Just because we can do a much more advanced job of targeting does not mean consumers want any part of it. In fact, we can be certain that they do not”.
So, what does the future hold? This remains to be seen. But a few options could include:
- A return to traditional targeting
- Door drop is currently undergoing a renaissance given the upcoming GDPR – non-addressed mail isn’t affected by the regulations, but remains a cost-efficient way to target households at scale. Could we see a return to assumptive insight driven channels like door drop? The finance services sector certainly seems to think so having increased spend in this channel by 18.5% in the last year.
- What about good old-fashioned strategy?
- We’ve all been found guilty of missing the point here in understanding the wider business objectives and striving for instant return in sales or income. So often strategy, such a pivotal part of the process is missed out.
Taking extra time to look at layering multiple data sources from campaign performance (channel, creative), CRM programmes, consumer behaviour (type, location, length, response type, consumer emotion) socio-demographic and size of market is fundamental to defining the strategy for both media and measurement.
- Amazing creative?
- Given the heavy number-crunching carried out in pursuit of a brief, it’s surprising how little insight filters down to the creative agency.
As agencies we all deliver the advertising to the consumer, but it’s the creative that the consumer sees, and takes an action from and this is the element that should be the culmination of all this insight.
- A stronger link between data strategy and creative?
- Do we as marketers have access to too much data to make decisions from and is this stifling our creativity?
I think the quote from this link sums it up, “The problem is that they find data boring. To them, data is rational. And great creative isn’t.”
It’s about changing the perception and the meaning of ‘data’.
Yes, data is rational, but it’s how you use it which defines whether it’s ‘boring’. As a planner, data excites me, I use data (significant and varying types from performance to attitudinal and behavioural) to put together successful campaigns for clients, so it baffles me as to how, as a creative, data can’t be viewed as exciting, utilising the myriad of insights available to deliver more relevant and engaging creative to drive campaign success is a massive benefit.
This is where our skill as marketers really comes in.
Just because we have this plethora of targeting options available, do we really need to use it in such fine detail – especially if the consumer doesn’t want it?
It comes back to truly understanding the consumer and delivering them a personal experience that not only uses the plethora of data that we have available but also understands their communication preferences – who they are, what the like, and, most importantly, what they want.