'How was your experience today?' 

A simple question, but still one of the most important to ask.  Companies today are advancing their methods for determining customer satisfaction - many airports, public service buildings and retail outlets are using customer satisfaction measurement terminals, which prompt their customers to select from a range of smiley face buttons to indicate how satisfied they were with a service.

 

 

As clever as these indicators are for measuring experience after the event, the challenge of actually ensuring customer satisfaction leaves many companies stumped.  Every organisation is different, as is every customer!  It’s important to take obvious steps (e.g. hiring friendly and helpful people, being upfront and honest, streamlining operations to reduce customer wait times and making sure to rectify any mistakes so customers feel heard and appreciated), but there isn’t a one-size-fits-all approach to overall customer satisfaction.

With recent advancements in analytics, however, there are ways to get a better sense of the makeup of your customer base and tailor your efforts accordingly.  Here are Datamine’s two overarching suggestions for how analytics can help you cultivate and measure a great customer experience.

 

1. Understand your customer

This seems like a no-brainer, but many companies haven’t actually done the necessary analysis to truly understand the different facets of their customer base.  In order to be able to deliver someone the best possible customer experience, you first have to know more about them - what is their age, gender, location and other demographic information?  What is their purchase history with your business?  And what ultimately drives their buying decisions?

Customer Segmentation image with iconsThese questions can be answered through customer segmentation analysis.  By taking a dive into your data and isolating/analysing individual customers (also known as ‘creating a single customer view’), you can begin breaking up your customer base into smaller groups that are similar to one another.  These groups can be decided based on the customer qualities that are most important to your business - for example, similarities in transactions, age, location, gender, buying patterns and more.

There are a number of different kinds of segmentations (strategic, marketing, operational etc.) you can employ depending on the nature of your business and customers.  Some segmentations are macro, others are micro - the type of analysis you need will determine the amount of investment, capability, back-end data, alignment of tactical aspects and number of tools you’ll have to use. 

Once you have individualised profiles for a number of different customer categories, you’re ready for the next step.

 

2. Use that data to deliver personalised experiences

When you’ve created single customer views and segmented your data, you can begin to deploy personalised marketing campaigns that are specifically targeted towards various sections of your customer base.  Research has shown that personalised buying experiences greatly improve customer experience.  For example, a 2016 survey from Accenture demonstrated that customers are more likely to buy from a store that:

  • Recognises them by name (56%)
  • Gives them recommendations based on their last purchase (58%)
  • Knows their purchase history (65%)

 

So how do you actually go about making your customer communications personalised?

The first step is determining what message you want you send to each of the segments you’ve identified, as they will all need to be approached differently.  In order to come up with the right message for each segment, you need to look at all the touchpoints in your business’ relationship with the customer (website, call centre, email, bricks & mortar outlet, social media etc.) and how they fit into that specific customer journey.  What are you trying to do for a particular customer?  What do they want from their relationship with you?

By creating qualitative customer ‘profiles’ for each of the segments, the marketing team can determine exactly what content is appropriate to present to each customer group.  The next step is to write queries within your marketing automation platform defining which message will be sent to which segment, when, where and how.

For example, let’s say you’re a retailer and you identify a segment of customers that haven’t purchased anything in five weeks (which is abnormal for your unique business).  You might send an email offer to these customers, tailored specifically to the individual based on their transaction history (such as a ‘buy one get one free’ promotion on the last item they purchased).

Naturally, these segments will need to be revisited and updated as the business grows, and it’s also important to analyse whether or not your personalised campaigns are working.  Are your customers more satisfied?  Are the personalised campaigns more successful than generic ones?  What needs to change?

 

‘I can’t tell if that was too much information...or not enough.’New call-to-action

We recognise that these two steps are very broad and somewhat vague - that’s because customer experience is one of the most comprehensive and complicated areas of analytics!  There are a myriad of different solutions that fall under the umbrella of ‘customer experience’, one of which is actually Marketing Personalisation as mentioned (and linked) above.

For more in-depth information about customer segmentation, check out Datamine's free whitepaper on the subject.  If you have a specific challenge regarding customer experience that this article didn’t address, feel free to submit a consultation request to Datamine - we’d be happy to take a look at your situation and recommend a solution.

 

Not yet convinced?

Here’s a case study where we used customer experience (CX) data to help one of our clients better monitor and optimise their overall customer satisfaction.

 

The Challenge

Tool iconHome improvement and garden retailer Mitre 10’s ongoing goal is to improve the shopping experience of its customers.  To support this initiative the company has measured a range of customer experience indicators across all channels of its business.  What was missing, however, was an ‘over-all’ customer experience picture – an issue Mitre 10 asked Datamine to resolve by collating and analysing its customer experience data and presenting it in a way that empowered the company to take action to address any customer experience shortfalls.

 

The Solution

Profiling icon Of the many customer variables available, Datamine selected a core range that would best represent the over-all Mitre 10 customer experience.  Included amongst these were transaction data, net promoter score survey results, customer memberships and loyalty swipe rates.  Appropriately modelled, these indicators formed the basis of a Customer Experience (CX) score for each Mitre 10 store.  The reports were also interactive, allowing adjustments to targets and new indicators to be added as required.  The relevant information is presented in a format that is easy for the stores to use and suitable for distribution to Area Managers and the CEO.  Every store received an over-all CX score, a summary of the core indicators used to calculate the score - and a 4-week comparison on performance measure.

 

The Results

Graph iconUsing the CX reports, individual stores can now track how they’re performing against CX targets (and in relation to other Mitre 10 outlets).  Armed with an up-to-the-minute customer experience score, Mitre 10 stores can take specific and immediate action to improve their individual CX indicators.  Since receiving the reports, individual Mitre 10 stores have been empowered to take greater ownership of their customer experience, resulting in improved CX scores across the entire chain.

 
 

 

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