One of the most important outcomes of consumer analytics is insights about your customers. Learn how to gain a new level of understanding to inform your decisions.
When I was young, my grandmother would always ask me, what's new? It's a great prompt. If you think about it, it's a great prompt for your business. What's new? What's new with your customers? What's changed for them? What are they interested in today that they weren't interested in yesterday? The larger organizations get, the more difficult it is to pivot and to move. But we have to do it otherwise we miss opportunities to provide value to our customers and to our shareholders. I really think that's the impetus behind the agile processes. Things change and we have to change with them otherwise we risk fast-moving competitors encroaching on our market domain. So what's new? These are the sorts of insights that we need so that we really know when to change. There are a few different ways that you can develop insights about your customers. The traditional way of going about it is polling and surveys. Engineer a questionnaire that aligns to the understanding that we're needing to capture, then we find people that represent who we need to capture that information from. My family and I were at a theme park recently and a pollster came up to me with an iPad and asked me three short questions. Wherever you're from. How often we visited and how we heard about them. And just like that, this organization had one family's information. I'm sure that pollster asked hundreds of people those same questions to gather more data. Again, this is a very traditional approach. It's how marketing research has been conducted over the past century. But there are emerged and emerging alternatives. Because there's so much digital information, we can now tune in and listen to what people are saying and what they are looking for. Take search data for example. If you're wondering what problems people are trying to solve, take a look at what they're searching for. Google trends, for example, provides publicly available relative data for just about any search query that you can think of. Google Ad Words as another example provides publicly available data and this is a great way to see what trends are on the rise and which are waning. But again, keep in mind that all this data may not pertain to your target population. Make sure you keep your target in mind at all times. So what's the advantage of this method? Self-reporting tends to give biased answers so the information you gather from polling has the potential to be skewed at least and just did wrong at worst. Now you don't run as much of that same risk with search data because it's actually what the market is expressing interest and intent in. The same could be said for social media analytics programs like sentiment analysis. This is a technique used to analyze text-based data such as customer comments. The way this can work is an algorithm parses the data and categorizes that information as positive customer sentiment, negative customer sentiment or neutral customer sentiment. So with these tools, you can ask, you can listen and observe to develop customer insights. So what's new?
- Designing a consumer analytics program
- Measuring a program's progress
- Governing your consumer analytics program
- Driving customer loyalty
- Improving the efficiency of your investments
- Using cloud computing platforms
- Machine learning for consumer analytics
- Data privacy, security, and ethics