Thinking out loud - Relevance, personalisation, tailored?

Some random, un-edited thoughts I found the other day when asked by a Marketing Director whether we should be talking about Relevance or Personalisation

OK so relevance and personalisation or tailored are much used terms in terms in the industry so I think we need to use something a little different and perhaps lends itself to our core offerings.

I quite like the term unique experiences in particular as it plays to our content and experiences pillar but also that the delivery of unique is achieved through data

Of course one angle we could play with is the idea of using our three pillars and data to understand and widen windows of relevance .

Relevance is important of course but I would argue that targeting or personalising customers based on who they are is less important than than targeting them at moments when they are ready to do something

The fact that I am just about to take out home insurance is more important than if I am a 35 year old male living in Newcastle. If I am existing policy holder then you could argue that the window of relevance in terms of me renewing that policy gets bigger as we get closer to the point of renewal. We can use data to understand when the best time to is to start explicitly talking about renewing the policy ( our business rules might tell us that this starts 30 days before the renewal date). But that fact that they might have had an unsuccessful claim in the last 12 months might require a slightly different approach)

A mobile phone customer might very well have a 12 month contract with you but does the fact that after 4 months their call volumes drop significantly suggest that the time to have a conversation with them about their contract has been brought forward?

A TV and broadband customer who is just 15 days into a 24 month contract already has an outstanding customer service issue and has been their account to search how to cancel a contract might mean that the courtesy call planned for day 28 might need to be brought forward.

Of course we can talk about upsides as well. The TV and broadband customer seems to be watching a lot of sport..does a conversation about HD become relevant?

A couple of who bought one of our new build homes has a new baby . Does a conversation about a bigger home become relevant?

Relevancy is important, but recognising those windows of relevancy is crucial. Its data that allows us to do this

These windows shift in time, size and shape

Of course we could explore how a brand can make these windows bigger...how does an insurance firm use data and content to be relevant to a customer in between policy renewals? How does a company installing boilers use data so they can investigate the relevancy of other services in between the lifetime of the boilers they sell?

Thinking out loud - Why aren’t we personalising more?

As marketers we have an abundance of statistics and research telling us that personalisation delivers in terms of customer expectations and ROI. The issue is that most marketers are faced with short term KPIs. It’s ultimately about this month’s sales figures and the quarterly board reports.

Justifying the ROI into personalisation (beyond just using a customers name) and automation is often difficult. Sales are relatively easy to measure (so we value that metric). The benefits of personalisation are of real value but often we find difficult to measure.

And of course, delivering the capabilities required takes time. Not every marketer walks into a job where the customer journey is mapped out, all of the data needed is in a single place and the technology needed is fully implemented. As a result it looks like a daunting prospect. Unless, a view is taken that we look at the road ahead but complete the journey in stages, building capability and stacking up the successes en-route. Perhaps looking at one channel at a time or one particular part of the customer journey.

Retail Personalisation

When we think of personalisation in Retail we obviously need to think of data. Traditional data in the form of Demographic, Profile, Behavioural and Transactional; but we need to consider the new boys on the block, Contextual and Emotional.

Contextual personalisation will allow marketers to deliver messages, content and experiences based on where the customer is. This might mean based on type of location – a retail outlet, whether that be on a high street or a shopping mall or other factors based around location, for example weather. For the former digital displays could now reflect the status of the store as well as the context of location and surrounding stores, whether they be competitive or complementary. In fact, those messages could also be based on the individual and their previous purchase history (Transactional Data).

The actual weather in that location can obviously be used to entice you into buying that North Face waterproof or a warming latte.

Understanding the emotions that a consumer is exhibiting in response to products (Joy, Surprise, Anger, Confusion?) will allow brands to target communications either real time or as a follow up.

For most consumers, omni-channel experiences are now a given, but the issue marketers have is recognising a customer when they are ‘offline’ in a bricks and mortar environment. The solution needs to focus on the thing we have with us 24 hours a day. No, not mobile phones, faces!

If we want to look to the future and how this might all come together then need to look East.

Brands in China and Hong Kong are using cameras with Facial Recognition capability (yes AI) to identify individuals and then combining for example online browsing history to allow informed conversations with store staff.

Alibaba and Guess have Fashion AI that combines facial recognition into ‘magic mirrors’ in changing rooms. It allows customers to essentially see what clothes look like on without trying them on. Recommendations on other options can also be based on local weather, gender and age .

But of course aiding a sale can also be delivered by making the transaction itself easier. Alibaba has launched an experimental cashier-less store called “Tao Café’’ where customers give permission for facial recognition to essentially to be used to facilitate payments without queuing. (Amazon Go’s queueless shopping experience has people queuing to use it!)

And a little bit less East, Zara is already experimenting with automated in-store order pick-up at its new flagship store in London’s Westfield Stratford shopping mall. Customers can scan their order QR code or provide a pin number to activate an automated warehouse behind the store, which uses robots to find the package and drop it into a collection mailbox.

The key is to use data and technology to deliver a customer experience based on who they are, where they, what they need.