May 17, 2023

Social listening, evolved

Date & Time (GMT):
May 17, 2023 12:47 PM
Date & Time (EST):
May 17, 2023 12:47 PM

Social listening offers a ton of benefits, allowing brands to listen to relevant conversations and hear what people are saying about them. But conventional social listening has its limitations, providing large volumes of unstructured data that users have to clean and interpret on their own. While this can work in organisations with skilled analysts available, it’s very easy to misinterpret the data and overlook key insights when you don’t have the right skill sets.

That’s where consumer intelligence comes in.

Consumer intelligence vs. social listening

Social listening enables you to extract quantitative data but it doesn’t go beyond this. It simply tells you that, for example, from October to February, people talk more about Scotch whisky on social media, and maybe brand X is more popular than brand Y.

Consumer intelligence is the next step. It’s about extracting meaningful insights from the data so that you can make better decisions. It tells you that people enjoy whisky for its warming quality during the cold winter months, and that they’re also interested in finding new whisky cocktail recipes. Furthermore, in the run-up to Christmas, it may also tell you that people need help choosing the best brand as a gift for the Scotch aficionado in their life.

AI-enabled consumer intelligence tech

To extract valuable insights out of unstructured data, organizations can use AI-enabled consumer intelligence tech platforms. These include a blend of modern AI technology, human expertise, data science, and market research. As such, they’re able to structure huge volumes of data much more intelligently. They give the user much more help in interpreting what the data actually means, so they can find those real insights that have true business value and business impact.

Setting projects up for success

There are a few key steps that will enable you to set your consumer intelligence projects up for success:

1: Understand your project background

Start by understanding the background of the projects. Understand the questions you’re going to answer, the objectives of the study, and how that insight is going to be used further down the line. This can make a big difference in how you deliver that insight and the type of insight that you’re looking for.

2: Identify what you want to answer

It’s difficult to structure the data in meaningful ways when you’re just listening to what people are saying without first identifying the questions you want to answer. The insights you get out of your listening efforts aren’t going to be very actionable. Here are a few examples of questions you can answer:

What do we need to do/say/look like to prompt people to switch to us?

How do we need to look to successfully reposition our brand from mid-market to premium?

What’s the consumer’s attitude toward change?

3: Identify what is going to be useful

When you have multiple data sources coming into one platform, it’s useful to assess the different use cases for which you’re using social data and then work out what data sources are actually going to provide value for you. Take the time to understand the different data sources and you can save yourself time in the long run.

4: Structure the data in a meaningful way

With raw, unstructured data, you get large volumes of confusing information. While it’s possible to conduct well-constructed Boolean searches to tackle the problem, it’s very difficult to completely eliminate noise.

Consumer intelligence tools, like Linkfluence, structure the data more intelligently by classifying the data into three levels of detail based on topic categories that are widely used across the digital marketing industry. For example:

Linkfluence more intelligently structured data

In this example, there will be no risk of false positives in the data because the platform has classified data points and can easily differentiate between Hamilton, the musical and Hamilton, the sportsman.

5: Interpret and socialize your findings

The next step is to interpret the data and extract insights out of your findings. This is when you try to understand what the things that you’ve analyzed are trying to tell you.

Next step to get started with consumer intelligence

To get started with consumer intelligence, start by auditing your current projects to understand what’s been happening so far. After that, you can begin to plan your first project.

Learn more about how to set up consumer intelligence projects by watching our on-demand webinar with Linkfluence.

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