Have you ever wondered why some businesses are finding it easy to engage and satisfy their customers? Well, we will let you in on a secret – it’s conversion analytics.
It’s true that customer feedback tools can help you offer customer insights to improve customer experience. However, customer feedback tools with conversion analysis features can offer you much more.
At the end of the content piece, you will understand the following –
- Conversation analytics definition
- How does it work?
- The type of feedback it process
- Importance of the approach
- Use cases of conversation analytics
What Is Conversation Analytics?
Conversation analytics is a data analysis technique to identify customer conversation insights. The customer conversations can be anything from phone calls to any medium involving dialogue.
How Does It Work?
It all starts with data collection. It has to be done from various channels like social media, phone calls, chatbot chats, etc. The data usually includes audio recordings, text transcripts, or digital transcripts.
In some cases, if the tools are advanced, they can collect metadata as well. This includes call duration, timestamp, and speaker identity. The collected data will be analyzed using NLP.
For audio recording, before undergoing analysis, it will be converted from speech to text first. An analysis with NLP will give insight into the tone, context, and purpose of the conversations.
What Type of Feedback Does Conversation Analytics Cover?
We talked about data collection and what kind of data will be collected for analysis. But, with respect to feedback, conversation analytics mainly focus on unstructured, unsolicited feedback. Why? Because it captures candid conversations and sentiments of customers.
Generally, there are two main types of feedback – structured and unstructured. Under each of these, there are two sub-categories, which are solicited and unsolicited.
Structured Feedback
This type of feedback is usually organized, quantifiable, and easy to analyze.
- Solicited feedback here is done through CSAT, NPS, and CES surveys. These are the results of direct and focused questions.
- Unsolicited feedback includes operational data collected during customer interactions without direct questions.
Unstructured Feedback
In unstructured feedback, you can find text and verbal communication with customers. These data are more nuanced and rich but, at the same time, harder to analyze.
The solicited feedback is mostly responses to open-ended survey questions.
It also includes the (direct) conversations (or engagements) with customers on social platforms. However, when it comes to unsolicited feedback, the data includes –
- Social media mentions and discussions but directly engaged by the brand.
- Verbal (phone) conversations with customers.
- Interactions with chatbot or human agents, but only those conversations that are not initiated by direct questions.
- Customer reviews on third-party sites like G2 and Capterra.
The data collected will be analyzed using NLP (as we discussed earlier) to understand the topics discussed, most used keywords, sentiment, and more.
Now that you have understood the type of data it collects, let’s see why it is important for businesses
to consider conversation analytics.
Why Is It Important to Analyze Customer Conversations?
There are many reasons why conversation analytics is essential for businesses. The following are the three reasons why. Let’s have a look at them.
Get the Complete Customer Story
A study by Zendesk revealed that more than 50% of customers use phones to connect with support. Therefore, just looking into customer feedback would mean tracking treasure using a burnt map. Or, in simple words, you will not get the full picture of your customers.
Therefore, it’s crucial for you to consider conversation analytics.
Boost Your Sales & Marketing
Apart from the support team, the sales team also directly connects with customers. This is done either by phone, email, or chat. Here, using conversation analytics, you can identify what persuades or dissuades the customers.
For example, some customer segments are engaged with a particular feature. But the same wouldn’t work with another segment. The sales team can use these insights to tailor their conversation and yield more conversions.
The same can be applied to marketing teams as well. Using these insights, they can also tailor their messaging to attract more prospects.
Best Way to Improve Overall Customer Experience
We discussed how conversation analysis can provide you with a complete picture of the customers. But we didn’t tell you what kind of customer insights this approach can provide. To give you a quick overview, here are the customer insights you can expect –
- The underlying customer sentiment to your product or service.
- Why the conversation happened in the first place (Eg, seek support or buy a product).
- Better categorization and response to customer issues and needs. The most discussed topic during the conversations.
- Extract repeating and most common (or rare) keywords in conversations.
Collectively, these insights can be used to improve your product or service and enhance the overall customer experience.
4 Use Cases of Conversation Analytics
We have discussed some importance of conversation analytics in the previous section. There, we have pointed out some key use cases of conversation analysis. Here are four more common use cases.
#1. Customer Behavior Prediction
Suppose you already have a product. You conduct surveys at regular intervals to gauge customer satisfaction and experience. Though the survey tool you use doesn’t have conversation analytics, the insights it offers have helped you.
However, the tool wasn’t able to spot the hidden sentiment (negative) of customers to a part of your feature. Since the feature collectively is doing well, you decided to expand it – specifically on the part that customers don’t like.
Imagine the reviews you could expect. Not to mention the effect on your brand image. But the fact remains, with conversation analytics, this could be avoided completely.
In other words, you could nib such issues at the root. The deeper customer insights provided by conversion analysis are granular and help you take preemptive action to avoid such situations.
#2. Customer Retention
With conversation analysis, you can understand the underlying customer sentiment, preferences, and pain points. You can take prompt steps to address these, take necessary steps, and improve customer satisfaction. And we all know satisfied customers tend to stay with the brand – leading to improved customer retention.
#3. Product Development & Improvement
As we discussed, the data will be collected across various channels. This includes but is not limited to support chats, social media, and online forums.
So, by analyzing such extensive customer data, you will get a comprehensive view of customers. For example, suppose you have about 100+ reviews on the G2 platform. Among that, around a dozen of them have left reviews about the lack of a certain feature that your competitors provide.
So, with normal survey tools, there’s no way you are going to learn about this. Another way is to go through each review to identify such feedback. And let’s be real, that’s just tedious and time-consuming. But with tools like proper conversational analytics tools you will not miss out on such insights.
Furthermore, you make necessary additions or improvements to your product as per customer preferences.
#4. Customer Service
Did you know that the average cost per call is about $2.70 – $5.60? Well, it’s true. Now imagine getting tens and thousands of calls every month for customer support. Expensive right? Therefore, it is essential for businesses to lower the average handle time and first call resolution rate.
Conversation analytics can help here.
It allows you to see agent behaviors, the point of friction, and the customer issues leading to longer handle time or repetitive calls. You can use this to significantly reduce the handling time and provide self-service content for most common customer issues.
CogniVue for Deeper Customer Insights
CogniVue is SurveySparrow’s newest addition to the range of features it already offers. It’s an extensive analysis tool that covers all kinds of customer feedback and provides actionable granular insights.
- Need to find the most [or the least] discussed topics? It has got you covered.
- Want to pinpoint the keywords present in feedback? Say no more.
- How does the customer feel about your product? Find the exact emotion behind their feedback.
- What about hidden trends and patterns? The feature helps you with it as well.
What can you expect in the coming days from CogniVue?
- Analysis of customer reviews across third-party sites
If you are interested in trying out the new feature – kindly connect with their team. So,
leverage the power of advanced customer feedback analytics and strive towards customer-centric business
growth.
