In 1950, Chrysler Plymouth struggled with the sales of its convertible. The data from a focus group indicated that it was wives who chose more sensible sedans over youthful, exciting cars. Chrysler realised that women buy and also influence the decision-making process of purchasing a car and it ultimately changed the way cars were designed, branded and marketed. Changing the target audience to women significantly increased sales and gave the manufacturer a more family-friendly reputation.
Bridging the gap between the moderators and the respondents, social media has transformed into a data paradise for companies who are shopping for consumer insights. The real-time availability, ease of access and low effort in aggregating the data, makes it a valuable resource for organisations. Although the pros seem to beat the cons, data from social media is still underutilised and its impact severely under-estimated. The question is “how can this data impact a business?”.
The main qualms against social media intelligence in comparison with traditional market research is that it’s neither representative nor systematic, some might say it lacks statistical rigour and has gaps in demographic details due to privacy factors. While all these accusations hold true to some extent, social media intelligence is not intended to solve the problems that traditional market research does.
Turn social engagement to relationship via direct marketing Match social data to first-party data (usually customer-relationship management) via identity resolution and profile enrichment for direct marketing. Once social data is made potent through identity resolution and profile enrichment, it can be used to feed into audience lists for omni-channel campaigns.
Scenario: Show return on investment (ROI) in sales to a successful social campaign
After a successful social campaign on one platform (let’s say Twitter), run the engagement list through an identity resolution engine to enrich the profiles with corresponding profiles on other platforms (like Facebook and E-mail). By comparing existing target consumer personas, it's possible to validate the right audience has been engaged. Next, we run targeted campaigns to this audience on other platforms apart from Twitter and capture consumer activity. This can help us accurately demonstrate ROI for social media effort.
Complement social data with other data
Complementing social media data with other available data sources can help you gather insights that impact your business. Today data is available everywhere. Picking the right data to complement social media data is important.
When you launch a new product in the market, social media can be your first source to understand user reactions and feedback. While this is accurate, data from non-core users can also result in bias. Adding data from focused communities (who are power users of your product) can give greater insight. Along with this, e-commerce cart data can be used to validate user feedback and analyse a user’s response to the issues. This combination can be used to triangulate primary research insights that were gathered from focus groups or intercepts.
Alternatively, when social media data shows a downward trend in user sentiment, we can use retailer reviews and Customer Satisfaction Score (CSAT) scores from e-surveys to validate the trend.
Marry social media data with location
Social media data and GIS (Geographic Information System) are good bedfellows. Together they make insights impactful.
The integration of social media data and maps are a great way to gauge customer pulse in the services sector. This is even more relevant in industries where hyper-localization is predominant, as businesses are looking for ways to personalize and fine-tune targeting based on locale.
While maps have been part of social media analytics tools, the usage is minimal and not been exploited to its full potential. Social data aggregators use various methods for determining the location of a post. Typically, geo coordinates are the best bet in determining the location of a social media post, but in its’ absence, the tools use various other info such as profile location, top level domain, time zone or IP address to determine the location of a post. Many tools in the market facilitate the collection of location-based data on social networks.
Apart from social networks (Facebook, Instagram, and so on), there are quite a few data sources that have location detail readily available. To name a few, online reviews, search data, retailer data, online forms, and so on. Below are a few use cases that highlight how businesses can integrate location and social media data.
Scenario One: Service responses at the speed of light
A global hospitality brand has geo-tagged each of their properties for social media listening. Each time a customer staying at one of their properties makes a social post on social networks (with location detail switched on), it’ll be seen by the command center.
If customers have an unpleasant experience during their stay. They are more likely to share it on social media. The social media command center, spots the content published on social media in real-time and immediately alerts the said hotel service staff and who in turn respond to the issue immediately. This delights the customer, and he responds positively on social media.
Besides, this data also feeds into the service delivery dashboard that helps the HQ team to understand the sentiment trends for each of their properties and identifies areas of improvement. This dashboard integrates data from different sources including online reviews, social, local suggestion box, and so on to give the executive dashboard a holistic view of the brand.
Scenario Two: Enhanced visual representation to draw insight
A consumer packaged goods (CPG) brand found that their product was losing sales volume in a particular market over a period of six months and wanted to investigate the cause. Can social data along with GIS maps help the brand identify the cause behind the dip in sales?
They plotted the customer sentiment generated from social channels along with corresponding sales data to develop a sentiment index. The data gathered from the index enabled them to identify a particular market which had a higher index (more feedback per 100 units sold). The sentiment trend also highlighted a spike in negative sentiment for the defined time period.
A quick topic analysis of the negative sentiment highlighted that many customers are complaining about packing of the products delivered. Pining the problem to the distribution process a map developed with sales, social and roadways data revealed that the particular market had bumpy roads. As a result of the insight gathered, the brand manager was able to connect the dots and speak to the distribution center to fix the issue.
“The world is now awash in data and we can see consumers in a lot clearer ways.” Max Levchin, PayPal co-founder.
From small businesses to multi-billion-dollar companies, everyone knows they need to be on social media. A marketer today cannot afford to ignore the data generated through social media as it is a key part of an organisation’s social strategy. Interpretation of the data gathered from social media is a critical aspect, as it brings the brand at arm’s length with its customers. An organisation’s ability to use social media data in engagements, products and service design determines its success in the market.
The author is a senior consultant-solution design at Infosys BPM.
The thoughts and opinions shared here are of the author.
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