4 ways retailers are extracting insights from their web chat support conversations

Delivering a consistent customer experience across every touch-point is still difficult for retail brands, particularly live web chat. In fact, contact center leaders say live chat is the most difficult channel to scale (36%). Yet savvy retailers like Saks Fifth Avenue and Rad Power Bikes have learned how to marshall data from their voice and chat interactions to improve the overall customer experience. 

Turning that same insight into action is where ChatAI Agents come in: purpose-built AI agents for customer service that read every web chat conversation in real time, surface the same sentiment and intent signals retailers dig for manually, and respond instantly with scalable, on-brand chats where customers feel heard.

These retailers are leveraging artificial intelligence to gain unique context on customer sentiment, unmet needs, and operational efficiency. At the same time, they are using technologies like screen-recording to gauge hiccups in the agent experience and provide work-from-anywhere agents with better training and workflows.

The result? Faster response times, improved first contact resolution rates, and increased brand loyalty. Here are some of the top ways retailers can leverage live chat analytics to drive business value.

1. Identify customer needs and frustrations

While it’s shocking to hear, today only 15% of the 200+ contact center leaders we surveyed in our Post-Pandemic Contact Center Report are using speech and text analytics to gauge their omni-channel experience. Yet savvy brands understand that voice and channels like live chat go hand-in-hand, particularly in the retail sector. For the shopper, it’s all one holistic experience. 

That’s why top retailers use artificial intelligence and keyword spotting moments, or points of interest within conversation interfaces, to monitor 100% of their voice and text interactions. From there, AI auto-suggests particular calls and chats that analyst teams should dig into, including instances of strong negative or positive customer sentiment, and long handle times. 

By doing so, these retailers can gain context on why some shoppers write into chat after attempting to call. Vice versa - they can also see which callers were unsuccessfully able to meet their outcomes by using chat with both quantitative and qualitative voice of customer data.

2. Reduce operational inefficiencies

As the pandemic continues and many contact center agents continue to work from anywhere, quality assurance - a long-time very tedious, manual process at contact centers - is suddenly taking center stage again. With so many interactions moving online from brick and mortar locations, it’s critical that retailers not only quality check their voice conversations, but also their chats.

With automated quality assurance Platforms, roles like QA analysts and supervisors will no longer have to identify what interactions to evaluate or where to look within them. Every single interaction is automatically scored and prioritized so they can focus on coaching agents. 

It’s never been simpler to QA voice and text interactions in minutes with built-in evaluation forms and coaching workflows. 

3. Provide custom-tailored training to agents

Did you know that retailers are actually ahead of the curve when it comes to investing in agent experience? According to our Post-Pandemic Contact Center Report, a whopping 54% of retailers are prioritizing agent analytics this year. That’s a higher percentage than any other vertical.

With a little help from AI, retailers are uncovering insights from their chat conversations, or text-based conversational interfaces, to do things like:

• Improve training documentation and internal knowledge bases by identifying topics that slowed agents down, led to supervisor escalations, or forced disgruntled customers to give up and call in.
• Enable self-coaching by providing agents with access to their chat transcripts tagged and time-stamped with moments of strong customer sentiment or silence. 
• Set and measure more ambitious performance goals by looking at the best practices top agents deploy to hit their KPIs, like average resolution time, and scaling those talk tracks/processes to the rest of the team.
• Better motivate, recognize, and reward top performance. 
  

With 72% of contact centers planning to hire this year in a challenging hiring market, investing in agent experience and technologies to enable agents is a MUST. 

4. Trigger missed opportunity and risk alerts  

For retailers, 2021 is the year they turn their contact center from a cost-center to a revenue generating machine. 64% of contact centers believe they already are generating revenue, and 85% hope to by the end of the year! But to do that, retailers need data on their top missed opportunities, many of which occur when customers use chat to get pre-purchase support, such as trying to locate where to find an item. The challenge is that too many retailers are missing these opportunities and not able to follow-up. That must change. 

With AI, retailers can get alerts on potential missed opportunities through chat so they can then integrate with their CRM and proactively follow up with customers. If they enable shopping and payments right within chat, they can also get alerts on compliance gaps and instances of potential fraud to better protect customer data. 

At the same time, they can go beyond CSAT scores, which do not always provide a full and accurate picture of their customer experience, to uncover additional revenue opportunities. For instance, YourMechanic noticed that some agents were receiving low CSAT scores, but when they analyzed the voice and chat transcripts, instead noticed that customers were disgruntled because specific products and services were not offered in shopper’s regions. They were then able to make the case to open up new revenue opportunities and unlock new markets.

How ChatAI Agents scale on-brand chat support for retailers

Manually mining chat transcripts for insight only goes so far once volume climbs. ChatAI Agents extend that same analysis into action, handling web chat conversations end-to-end as part of Observe.AI's broader positioning: Purpose-Built AI Agents. One CX Platform, delivering agentic AI for voice and chat to automate customer conversations.

Instead of routing every shopper to a queue, ChatAI Agents resolve routine chat questions instantly and hand off nuanced conversations to a human agent supported by Companion Agent, the evolution of real-time Agent Assist, so retailers get consistent, on-brand chat experiences at any volume.

• Resolve common retail chat questions, like order status, sizing, and returns, without making customers wait on a live agent
• Keep tone and messaging on-brand across every conversation, even at peak shopping volume
• Escalate complex chats to a human agent, backed by Companion Agent guidance in real time
• Feed the same sentiment and intent signals retailers already use for coaching back into the ChatAI Agent for continuous improvement

A big opportunity 

The combination of speech and text analytics alongside AI will be the driving force behind transforming retailers as we know them, particularly when it comes to live chat. Continuing to get more automated, more accurate, and more efficient, will accelerate opportunities from retailers.

At the same time, retailers will be able to better train and coach agents, which will make a significant impact on customer satisfaction, compliance mitigation, agent effectiveness, and most importantly, the bottom line. At this point, it's only a matter of time.