For any business, data is a great tool to understand your audience and their brand perception. Data helps inform decisions about marketing and the best ways to approach customers. However, because so many consumer interactions with brands are quick and social, it is tough to make sense of what you’re seeing. We’ll explain what conversational analysis is and how big data companies are utilizing conversational analysis to get ahead.
What Is Conversational Analysis?
The conversational analysis is a deep dive into social interactions. It explores conversations that happen between a business and its customers through such channels as social media, blogs, forums, and review sites. Where tools like brand mentions and Net Promoter Score (NPS) are useful for identifying customer sentiment, a conversational analysis gets deeper into insights and the why? behind the feedback.
As a business, knowing that a customer had a negative experience, but why they had it, helps to understand how to satisfy that customer and plan for the future. Conversational analysis is key to maintaining accurate data.
Putting Conversational Analysis In Your Organization’s Toolbox
Market research is a great tool because it provides quick, actionable insights into how a brand is perceived, both on its own and versus competitors. However, because market research is often conducted through scheduled interviews, it doesn’t 100% replicate a customer’s experience.
The conversational analysis is performed through avenues such as social media and customer support interactions, which will give a more accurate indicator of how customers feel about your organization.
Utilizing a conversational analysis to maintain accurate data can’t happen on its own, but when combined with traditional tools, it can provide a much fuller picture.
Examples of Conversational Analysis
Social Media
Many organizations have embraced social media to engage with customers, adopting a light and humorous approach. When starting a social media campaign, think about what voice you want customers to hear. Is it very serious or more irreverent? How do you want them to engage versus how do they actually engage?
Email is not as timely as social media but can still provide valuable insights. What is the content and message you are trying to get across? Do you encourage consumers to interact with you?
Customer Support
Whether you use a traditional customer support center or rely on a chatbot, customer support interactions are a key source of data for conversational analysis. What tone does your customer support offer? How satisfied are customers after receiving support? What’s the reason that the customer is contacting support in the first place? Each of those data points is valuable on its own, but, combined, they paint a much fuller picture and provide more accurate data.
Loyalty Programs
If your organization offers a loyalty or rewards program, this can add more layers of data to perform a conversational analysis. What percentage of customers sign up? How many stay active? What rewards do they choose? If customers choose gift cards for your business over something like a free t-shirt, it could indicate that customers are enjoying your products.
Benefits of Conversational Analysis
Conversational analysis can provide huge benefits to any organization. Here are just a few:
Deeper Engagement
In today’s culture, success is driven by deep customer engagement. Organizations that take the time to truly understand how customers interact with the brand and act on that feedback are well-positioned to succeed. Conversational analysis and the context it brings are key to that success.
Speed
Because you’re relying on customer interactions, new data is coming all the time. Analyzing this quickly will ensure your data is accurate and up-to-date, and you can continue to add to your base.
Product Development
A better understanding of your customers leads to a better understanding of your product. If customers react negatively to a newly announced feature or campaign, that may signal that you need to switch directions to minimize damage.
Cost
Conversational analysis software is available; however, even if you have limited resources, you can monitor mentions on Twitter, Facebook, or other social media outlets and dig into those case studies at no cost.
Predictive Analytics
Many big data companies are using conversational analysis to drive predictive analytics. If your company is using a chatbot, you can train that chatbot around existing feedback. If you know customers react in certain ways to certain campaigns, you can better target those campaigns and have a better shot of success.
Conclusion
With audience data being more available to businesses from more sources than ever before, it can be overwhelming to keep up and know your source of truth and the right way to go. Using conversational analysis with other tools and research will help maintain accurate audience data and help ensure that your business is heading in the right direction.
