Helping Small Retailers Make Sense of Their Data
Helping Small Retailers Make Sense of Their Data
Sadly, the reality is far from where it should be. Most small to mid sized retailers have databases with poor and incomplete data. Or misfired attempts in the past at running a few mailer campaigns with much money spent but little returns. Almost all our clients had experimented in some ways with mailer campaigns, referral or loyalty schemes. But results were typically poor to mixed in terms of response, sell-through and most important - driving sustained loyalty from the customer base.
What's heartening is - the fire has still not gone out. Most retailers (certainly from amongst our client base), readily acknowledge that they have been flying blind, and tactics have been misguided in the past. They continue to be vociferous supporters of the power of database mining, firmly believing the driver was not trained enough, nothing wrong with the car. Thankfully.
In fact most would today view their customer database as a source of competitive advantage designed to deliver a number of benefits including -
1. Get more customers (acquisition)
2. Keep these customers (retention)
3. Get them to spend more money
4. Recruit other customers through word of mouth referrals
5. Make the advertising and mailers more effective and cost-efficient over time
A good starting point is to baseline your efforts at the start of your journey i.e. write down what you believe you need to do to get a good customer database marketing program going. Your list should look something like this -
1. Identify the right customer for my mailing
2. Make the offer attractive and compelling
3. Make the messaging attractive
4. Make the timing perfect, and ideally coincide with a customer need
You might break it down further to say, these would in turn require me to -
5. Clean up existing database names, addresses, emails, mobile etc
6. Make sure from now on we are capturing clean data (...garbage in garbage out)
7. Send out timely reminders to customers... etc etc
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What emerges are 2 parallel tracks of activity that are ongoing by nature. A backend track that is focused on maintenance of quality customer data - completeness of names, accuracy of contact details etc. And a frontend track - that is focused on targeting the right customer, at the right time, with the right products and services, in an effective yet cost-efficient way.
While the customer database is your single biggest asset at the backend, the customer treatment plan becomes the single biggest asset at the frontend. The treatment plan is simply a plan that shows various segments of customers, and how and when they should be targeted.
By following established best practices in defining customer segments and creating customer treatment plans, companies gain rapid competitive advantage over their competition. Think of a neighbourhood customer with two retail businesses selling identical products. One business makes the effort to send out targeted and relevant communication, recognize the customer when he visits, setup appropriate reminders and alerts for this customer, and reward him appropriately for his business. The other does nothing. Who do you think will take leadership position in the customer's mind?
As businesses commoditise and differentiation decreases, the one with superior customer relationship wins. Gone are the days when customer satisfaction was the ultimate goal. Today its the price of entry. The real challenge is how to go from simple customer satisfaction to driving sustained customer loyalty. The kind that delivers multiple revenue streams with decreasing cost to serve.
Customer Data Analysis Ltd, is a group of customer management strategy consultants, provides services like customer segmentation, customer loyalty program, customer relationship management, data analysis software and data mining software.
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