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Every business knows that customer feedback is valuable. It allows us to learn whether a product has met a customer’s expectation and how we can improve our products.
Traditionally, there are two ways we can gather product feedback. We can ask our customers by conducting focus groups or sending out surveys, or we can wait for the customer to come us to through feedback forms on websites and customer support channels.
Asking the customer is undoubtedly effective, but it can often be time consuming. Depending on the questions you ask, it can also lead to biased responses.
Organic feedback from unhappy customers is less likely to but biased, but it’s also reliant on the customer contacting you. This type of feedback might only highlight negative or urgent issues. It’s unlikely that a customer will call your support line to tell you how much they love your product.
In both cases, it can often take a long time for customer feedback to make it’s way to your product development teams.
With rise of social media giving a voice to any consumer, the first few days after a product launch can be critical for success. This is when people are most likely to be talking about your products, and it’s the time you will need to react quickest to complaints.
Complaints about your products can escalate through social media. Apple learned this the hard way in 2014 when a few complaints about the iPhone 6 being prone to bending created a storm of discussion.
Aside from identifying emerging crises, social media is great for finding organic product feedback.
We like to share as much information as possible to help our users, and potential future users, get the most out of Brandwatch as possible.
So, in this article, we’re going to run through exactly how you can monitor social media to gain product feedback, using the Apple Watch as an example. Ready? Here we go.
Firstly we need to set up a Query to gather relevant mentions around the Apple Watch.
When we create our Query we can start filter out noise that doesn’t relate to consumer feedback. By using the NOT operator we can remove the irrelevant mentions. This will make it easier to identify the common issues.
To refine our data we can filter out Apple Watch mentions that aren’t from typical consumer channels such as news sites.
We only want to see conversations from Twitter, Facebook, review sites and forums, so next we’ll create a filter to only include mentions from these channels.
Sentiment analysis will gives us an overview of the ratio of negative to positive mentions.
Here you can see that the there are a greater proportion of negative mentions.
By diving into the negative we can start to get a better understanding of what issues our customers are facing.
We can also use topic clouds to identify common themes within our dataset.
Right away we can see a lot of mentions relating to scratches.
This could quickly become another #BendGate for Apple, so they would likely want to escalate this as a potential crisis.
Now we know some of the context behind the negative sentiment we can start to categorize our data.
We can create Rules to automatically group past and future mentions around common issues. This will make easier to gauge the ubiquity and urgency of each issue.
Some issues with the Apple Watch might not be apparent straight away. Unanticipated problems might emerge after future software updates, or Apple might find that negative mentions about battery life increase over time.
Using Alerts will keep you and any team member informed when that are shifts in your data, such as increase in negative sentiment.
Some issues may arise weeks, month and years after launch – you can’t anticipate every problem. Our intelligent alert system, Signals, makes it easier to stay ahead of emerging crisis.
Signals doesn’t need you to know what changes you’re looking for in advance – it analyzes your data in real-time, searching for anything that looks out of the ordinary. It’s great for unearthing issues you might otherwise have missed.
Social listening doesn’t just have to focus on surfacing the negative. We can also gain valuable feedback about what our customers like about our product or how they are using them day-to-day.
For a product as complicated as the Apple Watch, they are likely to be multiple departments, with each interested in different types of feedback.
Negative mentions about lengthy sync times are unlikely to concern the product design team. Likewise the software team won’t need to hear about issues surrounding durability.
Brandwatch’s workflow facilities ensures each mention gets the attention it requires. You can assign any issue it to the relevant member of staff or team so they can handle it, add notes and check it off when resolved.
Hopefully this has given you a decent overview of how to utilize social listening to gather important, actionable product feedback – in a fraction of the time you’re used to. We’ll be continuing this series of showing you to use Brandwatch to tackle certain tasks, so keep checking in to learn more.
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