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Seven basic techniques: How marketers can master customer intelligence

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26th Nov 2014
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Digital marketers have a huge consumer-shaped data mountain to climb. Having successfully converted potential interest into customers, they are faced with a variety of shopping habits, a whole host of different preferences and a complex web of intelligence to dissect if they are to maximise the effectiveness and profitability of consumer relationships. 

Successful consumer relationships are based on listening, appreciating and acting on preferences, interests and most of all, behaviours. Digital marketers are challenged with offering simple engagement that acknowledges all of this en masse. So how can they master customer intelligence and maximise the lifetime customer value?

Retention automation is the analysis and intelligent segmentation of groups of consumers who are then connected to automated campaigns designed to move them towards the purchasing of goods or services. Used effectively it can help brands retain, cross and upsell to existing customers who are already a lucrative, captive audience. A recent report by Forrester highlights vendors already helping digital marketers personalise customer engagement to increase lead conversion, customer buying cycles and loyalty and, in turn, increasing revenue.

Using data effectively is nothing new but it is an art many digital marketers are struggling to master. So how can they use and target information to run effective personalised campaigns?

In my experience, the following techniques are essential:

  1. Simple data collection

A solid retention automation platform should define simplified data and include only what is needed. It must also collect as much of this information as possible.

Basics include contacts, purchases and products via Recency Frequency Monetary (RFM) segmentation. Email, website and app behaviour must be included too and scripts implemented on a website or integrated automatically into a shop database helps data flow automatically. All this will help define what customers are doing now and will do in the future.

  1. Smart scoring and segmentation

Data in a focused structure allows predictive scoring models to be built to effectively segment customers. Engagement scoring can also be used to help win back defecting buyers with incentives according to their status and spend. But how can digital marketers get to know 100,000 customers in a defecting segment and hope to win them round?

They can’t and shouldn’t. However, the mass will have an aggregated personality which can be used as a guide. This will change over time and should be reflected in the marketing program.

  1. Smart metrics

Examining data can provide valuable insight, so using the correct metrics is vital. An example could be the assumption that if a first time buyer does not make a purchase within 90 days they will defect. However, closer examination shows this is likely after only 47 days - a far shorter timescale and reasoning to alter the digital marketing strategy. Predictive behaviour modelling can help highlight when this is required and motivational metrics should be used to assist digital marketers in auctioning this insight.

  1. Predicting revenue

Smart metrics can tell marketers how much money a defecting buyer is actually worth. By having a bird’s eye view of the revenue impact for actions, or lack of, potential opportunities can be spotted. Identifying this can help with campaign automation allowing digital marketers to monitor trends and reach conclusions they might not have previously considered.

  1. Put intelligence on a pedestal

Intelligence must be at the heart of a marketing platform which handles contacts, segments, automation, reporting and content. Without it results will be slow and therefore inaccurate. Digital marketers must aspire to have actionable insights in one interface or risk missing vital opportunities to analyse and act.

Content should also be fully integrated and every customer should receive communications which are relevant. Delivering this requires good campaign design and targeting of the right consumers with the right products.

  1. Meaningful reporting

Collect only what is necessary when reporting as this will clarify future actions. An efficient daily reporting routine should help manage contacts across lifecycle segments. This enables the personalities of customers to come to the fore and be tracked over time to identify potential revenue opportunities. Reporting should also look to monitor the impact of actions, indicating what works well and what needs to change.

  1. Experimentation

People are scared of change. Examining open rates, clicks and conversions will not always help inform a strategy but controlled group testing will. It renders accurate results and provides insight on how much a campaign is worth. This is not just revenue generated when a campaign is sent but revenue that can be specifically attributed to that programme that would not have been generated otherwise.

Knowing how to target customers based on experience is key to achieving metrics which are meaningful to the bottom line. Via these techniques, customised to each customer‘s behaviour, digital marketers can take smarter steps with actionable insights that create targeted, relevant and meaningful communications. In turn this will foster sales, relationships and brand loyalty. Consumer relationships must be mutually beneficial if they are to be successful and knowledge is crucial to establishing these.

Ohad Hecht is COO at Emarsys.

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MargeCLockhart
By MargeCLockhart
08th Nov 2019 09:43

Great tips for customer intelligence. Keep writing!

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