Customer Service & Dark Data The Insurance Edition

Dashbot helped extract customer signals from a major insurance company’s conversational data.
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When you hear the word “insurance”, what are the thoughts that come to mind?  If you’re like me, you respond with a deep breath.  

For some, it can be a yearly checklist item with peace of mind that it would lessen the burden in potential scenarios in the future.  While for others, even the thought of initiating the process can be daunting with questions about eligibility requirements, complex details around each plan, how to file a claim, you name it.  Add in the layer of sensitivity and urgency whether it’s a minor car accident or a major health crisis, conversations that take place with insurance companies can truly leave the person behind both ends of the interaction feeling….(fill in the blank). 

Whether you are an agent or a customer, these interactions may sound all too familiar.  So why do these interactions require more to fulfill a positive experience?  Each question a customer may be calling about will always be initially answered by an agent with, “It depends”.  

With each person’s needs being unique and policy regulations to be met, there is a lot that goes into consideration during these conversations to be: personalized to the customer, compliant with any policies, and transparent with explanations and decisions.  The cost of missing the mark in providing personalized, compliant, and transparent experiences (at speed) is the loss of a customer, employee, and time that significantly adds up to operational expenses and revenue loss.  

With 17 million contact center agents estimated worldwide, customer service costs are a common pain point for many organizations today and Gartner forecasts conversational AI will reduce contact center agent labor costs by $80 billion in 2026.  In hopes of driving costs down, and lessening the burden for agents, many companies have started to leverage bots designed to have conversations with a customer.  Problem solved, right? 

While designing a bot is a step towards the direction of deflecting more agent calls, building any new technology like a conversational bot is best leveraged with the customer in mind.  Why, you ask? We’ve officially just entered the era where tech advancements can enable automated service and for a highly competitive industry such as insurance, getting a customer experience right can be the ultimate brand differentiator. 

Conversational dark data is a crucial source of information that you already own and can be used to understand what customers are considering positive or negative conversations.  Because there is often a disconnect in how your organization sees the world and how your customers see the world, conversational data can play a key part in bridging that gap. 

Here’s how a Fortune 500 insurance company unlocked its conversational dark data with Dashbot to amplify its customer service innovation and reduce service costs.

Challenges for insurance & CX

High customer effort and costs for support

  1. Disconnected customer service experiences across chat, phone, text, and web. Siloed processes to file claims with an agent and submit photos separately through the website managed by a different team
  2. Poor agent productivity with high-volume and common claims support requests driving up agent attrition and contact center costs that could have been deflected by a bot 
  3. Lack of strategic insight with manual processes to review customer and bot conversations to design and improve bot conversation flows that meet overall service goals

The Solution: unlock customer signals from dark data

A data-first strategy

The top insurance provider and Dashbot partnered for a data-driven development strategy to start unlocking their dark data from their bot as one of the main conversation data sources to explore and discover customer signals. Once the bot’s data was connected to the omni-channel data platform, Dashbot’s advanced machine learning auto-processed the conversations from raw transcripts to a list of top customer support requests.  

In addition to top support requests, they were also able to visualize customer journey flows mapped by intent to understand the conversational paths at a high level and drill into all transcripts associated with each intent for more context.  Essentially, this unlocked a deeper understanding of the customer and the reality of the digital bot experience.   

With these customer signals discovered, the team could finally make sense of their bot’s traffic data and even make moves immediately with data-first to proactive service automation solutions.

Proactive service driven by data

Automating data processing with Dashbot’s ML quickly identified the bot’s top support requests and journey flows, empowering the team to take action to course correct the gaps that needed to be filled & initiate automation in places where they never knew existed. The moment of truth was learning that 80% of the bot conversations were out of scope for the bot to handle, leading to unhandled requests and frustrated customers. 

One quick win was proactively optimizing the bot to automate the top support requests that would otherwise result in an agent escalation:

  • adding/removing vehicle info
  • requesting a quote
  • making a payment
  • change of address

With the visibility into journey flows with the contact center, they were no longer deploying a bot based on assumptions and built the best path for first contact resolution. This resulted in a seamless route to transfer a customer to the right agent and department for faster resolution times.  

In less than 1 month, the insurance leader and Dashbot unlocked dark data and co-built a path for proactive service driving innovative digital customer service goals that improve CSAT, resolution time, and operational efficiencies.

Results: a clear path to digital service innovation

Dashbot’s role to centralize conversational data accelerated this insurance company’s vision for continuous improvement in digital experiences and enabled their teams to collaborate effectively. Unlocking customer signals from their bot data is only the start of discovering what their customers are telling them in other channels like their SMS data. 

Why the need for growing their unlocked data sets with Dashbot? In order to build the complete picture of the customer, consolidating all conversational data sources is a foundation to understand how to automate the holistic customer experience. For this insurance company, it truly starts with their customers as the source of truth.  

Unlock your dark data with an expert to understand your top topics around customer experience frustrations. 

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