Over 2 billion people are using messaging platforms such as Facebook Messenger, Whatsapp and Telegram making them integral in peer-to-peer communication today. As conversations over messaging platforms increase, chatbots are becoming an increasingly important medium for understanding consumer behaviour and for capturing important patterns in customer interactions.

The main advantage of creating human to machine interaction using natural language processing is that the machine can give immediate analytical responses. In contrary, a human being would take time to understand the situation and analyse the data before he responds and this analysis is itself subject to individual judgement. While delivering better customer service, chatbots also provide a way to integrate customer analytics seamlessly into your operations. In this process, they free your staff for other important tasks.

The advantages are more apparent when dealing with large data sets (that require longer to process). The efficiency, speed and accuracy of bots, combined with the underlying power of big data analytics can deliver significant value in a short period of time.

As Forrester concludes in their 2016 report – How analytics drives customer life-cycle management – “Every customer interaction leaves behind a trail of data waiting to be analysed”. These data pieces can come in several forms – text, audio, video, or interaction with a website or an app. In this article, we look at some key areas where chatbots can help companies tap into this intelligence.

 

Automated data collection

Customer analytics is the key to delivering world-class customer service. However, the process of gathering data from disparate data sources can be difficult and time-consuming. If the data is not homogenous, it can be particularly difficult to visualize and analyze.

To get deep insights into customer behavior, data needs to be collected from customer-facing interactions, real-time. This is where chatbots are of immense value. Every single data point can be recorded by the bot without needing any additional time or resources.

Bots could also automatically add to the knowledge about a customer by progressively asking him questions during his interactions with your app or website. When a bot collects data, it is updated instantaneously in central databases, making all the systems and processes aware of this newly gathered insight.

Integrating customer analytics into such interactions can provide you with real-time fixes, that can increase the customer experience considerably.

 

Opportunities for personalization

Personalized chatbots in Customer Experience Management Solutions

Chatbots, when fed in data from behavioural analysis, offer ample scope for personalization. For example, heat mapping and click tracking can be fed into the chatbot logic to increase the conversions.

Let us say you are an online retailer. Your heat maps and click tracking data tells you which product pages visitors click on the most, and from which pages they exit. Your chatbot can take in this data, and when the visitor is likely to exit, it can show them a pop-up asking, “Have you found what you’re looking for?”. This can keep the user engaged, and expand the conversion funnel.

As predictive analytics progresses and gives deeper micro-level insights into user behavior in real-time, chatbots become more effective. They can offer personalized suggestions to any user, based on analyses of similar customers, and predictions about this particular user behavior.

 

The case for different benchmarks

While analysing customer metrics (such as customer TAT, engagement time, etc.) from chatbots, it is important to understand how they must be treated in comparison to the same metrics from a different channel.

Chatbots in CEM improving business

As an example, consider the average customer engagement time (the amount of time for which the customer speaks vs chats) might be longer for a chatbot, compared to a voice channel. That is because of intrinsic delay that the text medium has, over a voice call.

 

Conclusion

As companies continue to increase their focus on big data, bots will increasingly play a bigger role in collecting new data and analysing it. In the future, we think bots will play a pivotal role in improving business processes and helping companies understand what drives their customers.

If you would like to understand how bots can help your business, please get in touch with us.

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