Real-time research insights are becoming something quite paramount to understand for both marketers and market researchers. The future involving machine learning, automation, and artificial intelligence will most certainly include more real-time data analytics.
Some might even try and say real-time data will become the new agile market research approach. But before falling head-over-heels for it, we must first uncover what really entails real-time research and determine how it fits with current research methodologies.
What Defines Real-Time?
When we’re talking about real-time research, it’s not the same thing as real-time results—data depicted through data visualization techniques as it’s collected in real time—though it can be. In some ways, real-time research is a modern method of ethnographic research since it also obtains information from consumers without explicitly asking them each time. The most commonly referred to example of real-time data is often social media listening. As campaigns, posts, or advertisements are launched, marketers can evaluate the performance of them and generate insights through real-time social analytics tools.
Real-time market research, on the other hand, is a unique data collection method that gathers information on a customer’s experience as it is happening. The need for more accurate understanding around consumer reflections and behavior gave way to real-time research.
However, accessibility to data because of the Internet of Things and big data made it possible. Specifically, the adoption of smartphones and its subsequent impact on cell phone usage has made it easier to gather data on a consumer’s purchase habits, location, browsing history, and so on, on a more consistent, real-time basis. As a result, the benefits of real-time research are numerous:
- The most up to date insights as they happen
- Unbiased results due to the unprompted nature of real-time methods
- Increased confidence with large data sets and sample populations
What Defines Agile?
There are a variety of definitions when it comes to agile processes. However, agile market research gets its roots based on the promoted iterative and incremental software development process. It encourages rapid and flexible responses from specific consumers—often done through the use of automation. This agile approach drives a quicker time-to-market, lower costs, and increased product quality.
Real-Time vs. Agile
Both agile and real-time market research have their perks. But real-time research specifically needs a careful approach when applying it to market research. Agile market research and most other market research methods are foundationally built with statistics, while real-time methods will be driven mostly by data science.
Further, real-time research is all about the reality of a customer experience, while agile market research takes into account the reflections of a customer.
In the end, it shouldn’t really be a choice between the two; rather agile market research and real-time data should complement one another. For real-time research to be used successfully in the market research industry, it must be coupled with primary research. Only then will we be able to use it in a more practical way. For example, as real-time data tells us when a consumer is browsing for a product, survey data can provide the prioritization of triggers and marketing activities that will encourage a purchase most.
Keep in mind that real-time market research is meant to be an additional source and type of data to provide a multi-dimensional look into consumers, and it won’t be applicable if businesses can’t adapt quickly to incorporate real-time findings. But taking it a step further, the possibilities of real-time research and agile market research together could mean a comprehensive view of a consumer’s past, present, and future behaviors at the speed with which they change.
To see an example of how a team at Google used agile, iterative research to quickly incorporate user feedback into several phases of development, download our case study.