Is your Voice of the Customer programme working hard enough?

This article, written by Neil Mason, was originally published on Clickz.com on 29/01/10 and is republished here with permission.

 Whilst on the topic of the last 10 years in web analytics (www.clickz.com/3636166) one of the major positive shifts in the past few years has been the emergence of the “Voice of the Customer” market. For far too long organisations tended to be too “site centric” in their approach optimising online performance believing that the solution lay in just knowing “what happened” and “when it happened” as opposed to “who did it” and “why they did it” – or more often than not “why they didn’t do it”. These days organisations are more aware of the need to complement and support their web analytics data by having insight into why people come to their site and what they thought of the experience. This is evidenced by the growth of companies such as ForeeSee Results at one end of the market (who recently reported a doubling in revenues over the last two years ) and the adoption of free tools such as 4Q from iPercpetions at the other. But having gone through the process of selecting or implementing a Voice of The Customer programme is it working hard enough for you?

Voice of the Customer (VoC) programmes have the opportunity to play a vital role in an organisations data eco-system. They can provide tracking data to look at performance over time as well as diagnostic data to drill down into specific issues. That data can be quantitative in nature such as Customer Satisfaction or Net Promoter Scores  and it can be qualitative, for example the comments left by visitors in responded to open ended questions. So VoC programmes can be extremely insightful but like any measurement system there needs to be an ongoing investment in order to extract the value. Often I have seen organisations who enthusiastically set up a VoC programme and are all over the numbers in the first few months but over a while the major output becomes a few top-line numbers that end up populating a monthly report or similar. Here are some thoughts about how to extract longer term value from your investment in VoC programmes.

Make it somebody’s job
This might seem like a statement of the obvious but any measurement system needs ownership. Somebody somewhere needs to be responsible for managing the programme and realising the return on investment. Often the challenge is that within e-commerce departments the skills may not already exist to set up and run such a programme. Those skills may exist elsewhere in the organisation but in any case a VoC programme needs to find a home. Someone needs to be responsible for ensuring that the programme is running properly from a technical perspective, that the questions are relevant and up to date and that the right insight is being extracted at the right time.

Look to integrate with other data
Any measurement system that sits in glorious isolation is not doing its job properly and VoC data is no exception. In the data world synergy is a reality and two plus two really does equal five. You will extract greater value form your VoC programme if you actively seek to integrate with other data. At the simplest level, integration can mean working with two or more datasets side by side. An example would be looking at the funnel from a web analytics systems and looking at reasons for not achieving goals from a VoC programme. Alternatively it might be starting with some specific comments left by visitors in a VoC programme and then investigating their behaviour in a tool like Tealeaf or other customer experience measurement tools.

At a more complex but more powerful level, you can look to physically integrate the data by creating a link between the VoC programme and your web analytics system. Many of the major measurement systems in each area now have data integration capabilities. These mainly allow key data from the VoC system to be captured into the web analytics database and reported alongside the usual web analytics metrics. Having with the segmentation capabilities built into most web analytics systems these days, it also allows the analyst to look for relationships and patterns between people’s attitudes and option and their behaviours. For example, are people who land on our marketing landing pages more or less likely to achieve their goals than people who land on the homepage?

Actually listen to “The Voice”
Whilst a lot of value can be gained from systematically tracking various different customer orientated scores, a huge amount of value can also be mined from the comments that visitors leave when asked for their opinions on issues or reasons why they did or did not do certain things. Depending on the scale of your programme you might have a lot of valuable feedback there which is often left to gather virtual dust in the bowels of the system. The trouble with this data though is that it’s not structured and so it can be difficult to extract sense and meaning from it and also there can be a lot of it.

Some of the higher end VoC programme services have developed or are developing algorithmic approaches to analysing free text data and trying to quantify the “sentiment”. However if you programme is more modest then there is no substitute for the human brain in terms of making sense of free text. When you set up your programme make sure that you read through the comments that people are leaving. Quite quickly you will get a sense of the main themes that are coming through. Note these themes down and then quickly tot up how many comments relate to each theme, this will give you a sense then of how important or how widespread these issues are. If you do this on a systematic basis, every day or every week, then you can also build up trends of how these themes are changing over time.

Hopefully these thoughts will help you to extract more insight form the investments you make in understanding who your visitors are, what they think and why they do the things that they do (or don’t do…)