Real-time contextualisation is here

Your customers are engaging with your business across an increasing number of touchpoints – websites, social media, in-store, mobile and tablets.

But regardless of how they engage, they expect a customised, personalised, and consistent experience. This expectation continues to be a challenge for businesses, which have to manipulate enormous amounts of data to try to understand how to effectively engage each individual.

In this landscape, data needs to be collected and analysed in real-time, and any data needs to be instantly actionable, preferably in a predictive way.

Without these capabilities, marketing messages are less compelling and response rates fall. Conversely, those brands that embrace real-time contextualization through powerful and flexible big data see huge uplifts in campaign responses.

Marketers are now recognising the imperative of these omni-channel, contextualised communications with their prospects and customers.

The omnichannel experience – Burberry was a pioneer of ‘clientelling’ in-store to build customer data.

burberry

There’s no excuse for generic experiences

The happy customer isn’t just a customer who wishes to purchase more, it’s a customer that is retained, upsold and – perhaps most importantly – the customer who becomes an advocate for your brand.

Even so, how many times have you heard your peers and colleagues complain that they don’t have proper analytics capabilities, which means that they are limited in ROI view, optimisation and progressing the digital experience?

Or that connecting all the activity and data across multiple channels and departments, and unifying them for monitoring measurement, evaluation and future marketing activity is challenging?

And how about that disparate systems and data make it hard or impossible to personalise campaigns and gather, test and analyse customer data? 

In my mind those are pretty flimsy excuses. There are powerful customer and marketing analytics tools out there, and many will enable marketers to understand their customer’s behaviour not just by answering questions, but by asking ‘what can I do with this information?’

How well do you know your customers?

Can you answer the following questions?

  • Do you know how many people visited your stores, purchased, or left without buying?

  • Do you know how long it takes for a customer to make a return purchase, and then another?

  • Do you know when a customer becomes inactive or lapsed?

  • Do you know what your most loyal customers look like and how to find more of them?

  • Do you know how to apply what you learn about your customers – what/ when/ where – and turn that into personalised conversations?

  • Do you know how to monitor changes in consumer behaviour and act on this quickly?

  • Do you know how to use affinity reports to not only determine ‘the knowns’, ie. people who buy this also buy that, but also ‘the unknowns’ – affinities which don’t conform to a set behavior but proffer new marketing opportunities, through those affinities, brand, product or otherwise?

  • Do you know how to shadow customers to determine when the right time is to contact them – learning their propensity to buy? 

  • Do you know how to track trending behaviours, such as identifying ‘repeat refunders’ or repeat returners – for example customers that buy three items online and return two in-store?

Time-tested models such as RFM are all about actionable data.

rfm matrix

Marketers need to be able to act on data

Marketers need to be able to act on data not just pore over numbers in spreadsheets – there is a difference between a data question and a data driven insight with targeted call to action.

In my mind, marketers need guidance about what is relevant – what are their customer indicators, what are their churn indictors – and how to action all of this in an automated fashion.

Basic reporting, such as how many customers shopped online, how many abandoned a sale etc arguably add to the volume of data out there, but it just adds to the information that marketers struggle with.

As a marketer, you should ask yourself the question – if for example you knew that 40% of customers who shopped in the last 3 months were new to your brand, and out of those, 10% have bought again and most within two weeks of their initial purchase – would that be a valuable insight?

And if you could then use a tool that identifies all those new customers who have not repurchased by two weeks and automatically re-engage with them leveraging relevant content using your marketing cloud software, would that be beneficial to your business?

If the answer is yes you need to consider using the technology that is out there, to help move you towards the ultimate goal of providing only relevant and timely content and marketing messages to each of your prospects and customers.

Remember that building your marketing strategy on a solid customer data foundation will pay dividends for years to come.