Just a couple of decades ago, marketers were thirsting for digital data. Today, many of them are drowning in it.
For data to matter, marketers must analyze it and turn it into insights. It feels like a tall order, dealing with so many disparate data sources.
Marketers still have far to go in really taking advantage of all of the data available to them. For example, according to Forrester Research, only 19 percent of marketers integrate social media data with customer-relationship-management data, and for in-store data, that figure decreases to 16 percent.
Social data can be a gold mine of insightful information, but only for marketers that know how to use it.
Even by itself, social media data can be used in numerous cases, but some of the most impactful opportunities lie in integrating social data with other data sources (such as data collected in-store or through call-center phone conversations) and analytics technologies. The following examples illustrate how companies are using social data to great effect, and these practices are worth emulating.
Social listening sheds light on brand sentiment
Most brands monitor their social media notifications, keeping up-to-date with tags, comments and other customer interactions. However, there’s much more to the conversation.
Social listening is an analysis of the overall conversation—the brand sentiment—which you can use to generate actionable insights.
To figure out who’s talking about a brand, marketers can compare the interests of the talkers with the rest of the social media population.
When Chipotle made its entire menu GMO-free (genetically modified organisms), the company used social listening to analyze what customers thought about the move and who even cared about it. Chipotle marketers saw that users tweeting about their non-GMO menu were more interested in topics like Monsanto, agriculture and climate change than the Twitter pool at large. That’s how they knew their message was resonating with the right audience, and social listening tools added valuable consumer sentiment insights.
From the data, marketers gathered that sentiment was 42 percent positive and 31 percent negative with this target audience.
Contextual and social data combine for personalized insights
Integration empowers marketers to create context-based content like never before. One company, Flybits, now offers a cloud-based, context-as-a-service solution called Experience Studio that enables companies to provide personalized experiences to mobile users. Tools like this one allow marketers to see everything from consumers’ social behavior to weather conditions in their location, so companies can get hyper-specific with their digital outreach strategies.
For example, if a mobile user is approaching a movie theater and it’s pouring in their area, the theater could combine location and weather data to recommend a movie as a great rainy-day activity. Or if a user has been raving about a particular coffeehouse on social media, it might send an offer to their friends nearby that says, “Your friend Joe loves us. Come check us out for 20 percent off.”
Social prediction enables market trend analysis
To maximize the utility of user-generated content and other social data, many brands are turning to artificial intelligence and machine learning to predict the direction of future conversations and trends in their target markets.
PepsiCo, for instance, uses a social prediction tool known as Trendscope that compiles public data from a wide variety of sources in order to inform its future product releases. The strategy has already borne fruit in the form of trendy new snacks, such as salted pea chips, that you would typically expect to see in a high-end health food store rather than next to a Pepsi can.
Social prediction lets brands get ahead of the trends instead of playing catch-up. According to PepsiCo strategic insights director James Howarth, this tool enables cross-department collaboration: “It allows us to then have a conversation with our sales and marketing teams, where we can say here are the two, three or four trends that we think have really big potential.”
Social media data in its raw form is unstructured, and marketers must mold it into manageable data sets in order to unlock its potential. The most successful companies are using tech to integrate and analyze valuable data for stronger brand strategies, personalized messaging and powerful predictions.