Information online is abundant with emotional and strategic signals. Processing all this data, separating it into buckets of your interest and extracting relevant insights on a certain brand relevant narrative is an awesome superpower to have.
Once reliant on traditional methods like focus groups or surveys, market research is now an inflection point. A range of new tools are emerging to help with tasks to save time, cover more ground and find dive points faster in troves of online chatter.
The cultural norms, especially driven by additional focus on digital lifestyle are changing rapidly. Users online are much more comfortable publishing what they are feeling and it is about something they actively engage with in real or virtual life. Plenty of data to tap into and dissect.
Now you have no reason to leave all that data behind, but get ready to dive head on into an ocean of insights related to your specific narrative themes. ---show using emphasis like style of theme.
Here, we showcase an example of how talkAItive helps you learn emotional contexts related to a specific narrative i.e. online shopping in 2020. We expect this to be an excellent source for your businesses to use for differentiating and continuously improving their offer in their online ad spend, content strategy and crisis management.
Both primary and secondary research which can benefit from extracting interesting contexts from social media, online or internal sources (reviews and survey text responses, emails, support chats). A tool which allows you to pick your own search terms, sources and time frame and returns top emotional contexts across all text based data is a deserving assistant for any market research based campaign.
We don’t discount the importance of surveys and focus groups, as they have established their own methodology and are transforming as well through the use of AI and vision technology. However, bias is an issue that needs to be addressed on these survey forms and focus group strategy. In this article we showcase how talkAItive can help you pick topics of interest which can drive your survey and focus group strategy.
Key Contexts Found: Experience
Using search on client chatter, we found that for “experience” there were about 1,100/6,014 approx 18% of total chatter. This makes this a good candidate for further observation. Across the sentiment spectrum of most hated to liked there are a variety of satisfactory accolades to a small business #Sheels to aspirational wish form more “retail virtual experience” and very direct negative reaction to persistent nature of “ads based on browsing and purchase behaviour”. All these three emotional contexts are very far apart in the nature of related emotion as expected. Mention of “AI in retail” made it to the top ten of the emotional context list. All these are examples of emotions expressed related to online shopping or purchase based tweets.
Below are examples of these tweets related to summary above:
#Sheels is one of my favorite sporting & outdoor stores to shop at. Employees owned & operated with selective locations.
"As we are getting lockdowns and industries are losing, shops should create a VR VIRTUAL SHOP so the experience of buying online will like MORE REAL and pleasent.
The incessant thirst for feedback makes buying online irritating. Back in the day if you bought a Twix you didn't have the newsagent chasing you down the road with a feedback form, pleading you give your experience a score out of 10.