While many of us are just drowning in work these days, there may be some of you that actually do have some extra time on your hands because your budgets and perhaps projects have been cut due to the economy. So in the spirit of doing more with less, I would suggest that you focus inward and do more with the data you have already collected. This type of analysis is really great for customer satisfaction and loyalty study data. But it can work for other usage and marketing research data as well.
So what are you going to do with the data you’ve already collected? Here are my humble recommendations:
- Combine your data—When I was working for a well-known energy company in New Jersey, we had years upon years of customer satisfaction data on many different types of products, such as electric repair, gas repair, appliance repair, metering and so on. It’s amazing what we found we actually looked at the data side by side. I would have liked to combine all the data sets to do further analysis, but alas I lacked the time (and patience). As long as the types of customers you are combining aren’t meaningfully different and you have some overlapping questions, you can combine the data. Once you have combined the data, you can use SPSS or SAS to do further data segmentation; as you will probably have enough data on each of the demographic and psychographic variables to do a more meaningful segmentation than you were able to do for each product alone.
- An exercise similar to the one listed above would be for you to combine several years worth of data for one product line and run your segmentation models on that data to see if anything meaningful “pops”.
- Compare different respondent types on similar questions—another meaningful comparison is to chart data from dissimilar but related respondents. For example, at the insurance company I work for, I run two different customer satisfaction tracking studies: one among small businesses and one among our appointed agents. It is very interesting to compare how small businesses perceive an issue and how agents feel about that same issue. There is usually a unique education and/or sales opportunity when the two segments don’t agree on an issue.
- Add company events and other influencing forces to your data presentations—by showing “outside” forces and key company events, you may be able to uncover a key driver of satisfaction or loyalty that is environmental based rather than customer service related (and hopefully controllable) that was not evident without having these key forces and events included in your data reporting.
So as promised, I provided you with a few basic things I have tried to do more with less. I would love to hear about how you have done more with less!