Meet John, a product planner at an automotive original equipment manufacturer (OEM), who is responsible for taking brand and feature-planning decisions at the front end of new product introductions. John is confronted with a few questions. First, what are his customers needs and pain points? Second, what trade-offs do customers make during a vehicle purchase decision? Third, how do customers perceive his brand and those of the competitors? And finally, what do customers perceive as value for money? Product planners or managers across various industry segments, like industrial goods and specialty chemicals, tackle similar questions.
Executing a customer-centric product-planning strategy
We worked with John to help him answer the business questions he raised. Johns team had limited sets of qualitative data (in the order of one thousand), gained through traditional methods like focus group discussions and syndicated reports from market research agencies. The team was keen on understanding how customers look at the companys competitors product offerings, and wanted to leverage the intelligence to tailor the value proposition of their own products in the pipeline.
Gaining intelligence on competition
We profiled select competing brands using social media listening tools, collecting about 80,000 mentions or posts across different social media forums, including professional automotive blogs. Through an entity extraction technique, we extracted data clusters that contained data sets on features, needs, and pain points, and analyzed them banking on automotive taxonomy. While sentiment analysis is omnipresent in brand engagement analysis, we decided to add value through contextual reports.
We identified customer expectations for each feature in the form of different categoriesmet, missed, and exceeded. One observation was that 40%, 20%, and 10% of the users of a competitor brand gave thumbs down on exterior design or styling, underrated engine power, and fuel economy, respectively. This insight created an opportunity for Johns company to focus on these factors.
In another instance, we looked at the alignment of users voices with that of competing brand campaigns to understand the actual positioning of the product. One brand spent about 19% of campaigns in positioning its pricing as competitive; however, about 28% of users disagreed with this message and opined that the product is overpriced. Similarly, 30% of users were unhappy with the engine knocking sound of a car. More importantly, it was found that a surge in negative sentiments have a strong correlation with a decline in sales, and the reasons can be pinpointed too.
Putting your customer firstand at the core of your business
The project resulted in proactive, customer-centric product planning. While in this case social media analytics was used to analyze competitor products, it could be used to analyze the firms own products too. Correlating insights with enterprise data like customer demography, purchase history, dealers voices, and service patterns will help compound business value.
With social media bringing consumers and businesses closer together, understanding customer preferences and making customer-centric decisions will help businesses ride the next wave of growth. Welcome to the age of social media data-driven decision makingI see exciting possibilities! Do share your experiences or business challenges in introducing new products.