Sentiment data is a growing metric for marketing departments.
The positive, negative, or neutral conversations happening around your brand can help you understand buying propensity (among other things).
But what about sales? Sentiment data can also be used for things like better targeting and social selling.
Here are a few unique ways you can start using sentiment data for better targeting and sales.
Understanding Sentiment Data
Sentiment analysis, otherwise known as the feelings potential or current customers have about their interactions with your brand, is hugely important to differentiation.
Marketing and sales departments often know what happened, but they have a harder time answering the “why.”
- Why do customers buy from us?
- What motivates (why do) potential customers to buy from our competitors?
- Why is product/service X underperforming?
Answering questions like the above are imperative to business and is where sentiment plays an important role.
Additionally, sentiment has benefits surrounding …
- Business diversity. Sentiment data is not just for the marketing department! It can be used for marketing & branding, social media monitoring, HR (voice of the employee), customer service and/or customer care (voice of the customer), and sales.
- Scalability. The amount of time it would take humans to manually sort through thousands of tweets, customer support conversations, and customer reviews should make your head spin. There’s just too much data to process manually, but with machines doing the heavy lifting, you can use intelligent tools to scale — and fast.
- Real-time data. A tool that helps you track the sentiment of your customers can immediately identify issues and help you put a human on the case — all in real-time.
Measuring sentiment, however, can be tricky.
Measuring Sentiment Metrics
Of course, surveys are one way sales teams can collect customer sentiment. However, companies should consider other sources for sentiment data as well.
We also use social listening to detect sentiment.
With sentiment, you should most be interested in understanding and measuring the feelings and attitudes of customers. Three common ways to measure sentiment are through:
- Frequency. How often does our customer or would-be customer provide feedback? How often does our customer or would-be customer interact with us on social?
- Volume. How much time does our customer or would-be customer spend offering feedback? How much time does our customer or would-be customer spend interacting with us on social?
- Weight. Are our customers’ or would-be customers’ thoughts and feelings positive or negative? Are they neutral? Why?
Using Sentiment Data For Sales Targeting
First, create profiles to identify the different sales groups who buy from you. With a target list of would-be customers who are likely to buy, imagine how much more targeted your sales efforts would be.
Setting that up through sentiment data may look something like this:
- Define sales accounts based on revenue and customer input. Form two groups: closed business and non-closed business.
- Next, use sentiment data to fill in data on the two groups. The sentiment data should reveal the feelings among those in the closed and non-closed groups. (think word clouds, positive vs. negative sentiment, trends, etc.)
- Third, identify the people in the non-closed group who showed positive sentiment data around your brand/product/service (meaning, they should have been won over, right??). Make this group your target group.
- Finally, use sentiment analytics on your target group. You should start to uncover conversations, feelings, and thoughts around why these customers have not yet purchased. (think word clouds, positive vs. negative sentiment, trends, etc.)
Going forward, notice the patterns and trends emerging among both your buyers and potential buyers.
Use this ongoing process and data to inform sales efforts.
Preparing For Sentiment & Sales
Most importantly, gathering customer sentiment data is becoming increasingly complex.
Customers share their thoughts and feelings in a variety of ways, including customer service systems, social media, through their dedicated rep, and/or through surveys.
Today, sales teams primarily rely on surveys to collect and understand sentiment data. In the future, the ways in which you collect sentiment data must evolve.
In addition, both marketing and sales teams need to create environments where potential and actual customers can share real-time feedback.
Are you using sentiment data for marketing or sales activities? Let us know in the comments section below!
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