Marketplace customer reviews
Consumer reviews are probably the most valuable sentiment data any digital retail business could collect, and analyze. It is here that customers divulge exactly what they like and dislike about products, enabling businesses to be buyer-driven. A good example of this is a company involved in selling portable speakers. By scanning industry-wide customer reviews, they may learn that a large majority of consumers appreciate speakers that:
- Are waterproof
- Have long battery life (24 hours +)
- Are purpose built for outdoor use
While a fair percentage of clients dislike:
- Larger devices
- Complex setup, and bluetooth connectivity
- Speakers that don’t have ‘sound mix’ options (e.g. equalizers, bass dominance etc)
This customer feedback qualifies as the most accurate consumer sentiment available to companies. Once analyzed based on factors like geography and age range, companies can decide how to leverage this information. They may decide to optimize their product features or change listings/marketing campaigns to highlight the things target audiences are looking for.
Social media mood
Social media is another place where consumer sentiment can be discerned. This could come in the form of a:
- Video product review/unboxing on YouTube
- Post describing an individual’s experience with a new item on social media
- Dedicated Reddit thread discussing an entire item category such as ‘Gas-based BBQs – dos, and don’ts’
By scanning videos, posts, and threads for recurring ‘social sentiment indicators’, businesses can start stitching together a user-generated market picture. For example, if unboxing videos are increasingly negative or disappointing due to the fact that an ‘add-on’ such as a cable is missing. Companies can work to include this, sending this missing part to a disappointed influencer who can then go live and give the company in question positive follow-up feedback.
Search engine trends
The way in which people interact with search engines is a powerful way to discern sentiment. Most consumer journeys begin with a search query. When those are aggregated and analyzed, a clear picture can be painted of the collective industry questions currently being asked. So, for example, a company operating in the automobile industry may discover that consumers in the US are searching for the following:
- Are electric vehicles (EVs) really cheaper than gas?
- Does the government offer tax breaks on electric cars?
- What is the difference in terms of the carbon footprint of an electric car, and a gasoline-based one?
This can highlight the fact that many consumers are skeptical and/or ignorant about the merits of owning a non-fossil fuel-based vehicle. This insight can enable EV companies to create educational webinars, blog posts, and courses to help educate, and ultimately convert target audiences.
Competitor listing analysis
Another rich source of consumer sentiment can be analyzing competitor listing performance data. This may include:
- Seasonal sales trends
- Correlations between promotions, and Sell-Through Rates (STRs)
- Seller ratings
These data points can be representative of what consumers think of certain vendors as well as what external factors affect positive purchase decisions (especially emotional or spontaneous shopping decisions). Sometimes a correlation can be found between two data points that point to unplanned purchase decisions, such as:
- The changing of a listing item image and a spike in sales
- Price point fluctuations and an increase/decrease in STRs
- A change in a seller’s ratings, corresponding with higher than usual Click-Through Rates (CTRs)
The bottom line
Being able to collect consumer sentiment data enables companies to:
- Optimize product features, and marketing campaigns
- Detect negative feedback, having the opportunity to correct course
- Identify informational gaps giving companies the space to educate and convert target audiences
- Cross-reference data points from competing vendors identifying new paths towards a positive purchase decision
But manual data collection can be a resource-heavy endeavor which is why so many companies are now opting for a fully-automated data collection solution.