Customer Experience Quick Wins with Conversational AI

Customer Experience or CX as it is now commonly known is fast becoming a growth space in organisations. Gartner reports that “Seventy-four percent of organizations expect increases in their CX budgets in 2020”1.

Why? Businesses can accurately quantify the impact of CX in their organisation. “Seventy-five percent of organizations are now able to show that customer satisfaction leads to revenue growth through increased customer retention or lifetime value.”1 This is also leading to new roles being created like the CXO (Chief Experience Officer) and CCO (Chief Customer Officer), or focused CX responsibilities sitting under the CMO.

This shift has organisations looking for new ways to give them an edge to improve any customer touch point.

If you’re new to Conversational AI or even new to your role in your organisation we have pulled together three examples of how Conversational AI can provide quick wins while setting a solid foundation to build upon. The ultimate goal is to move from pilot to production use cases with the KPIs and measurements you already use to demonstrate positive change within your organisation.

Conversational AI can be rolled out across marketing, sales and customer service making it an effective tool to improve CX when implemented correctly across the whole organisation. The impact can be measured and directly correlated to revenue gains, expense savings and improved customer satisfaction.

Three examples of how to implement an improved CX with a Conversational AI:

  1. Reducing initial response time
  2. Setting customer expectations
  3. Enriching the data

Step 1: Reducing initial response time

As soon as a user reaches out with an enquiry you have an opportunity to respond with a personalised message that’s delivered immediately. This gives you the opportunity to frame the conversation, educate about the services you provide through the channel while keeping the customer engaged.

Next steps, when rolling out from a pilot to production this example could see you expand the capabilities of the system, using this message to route the conversation to the correct team or department based on some natural language understanding.

Step 2: Setting customer expectations

Setting expectations is a key to improving an experience, while it may not be an immediate and ideal outcome for the customer, they know what to expect. If you’re not able to achieve your goals for customer interactions on day one, this can buy some time and give the customer an immediate understanding of the experience they can expect. It can be as simple as handling office hours gracefully so people who enquire out of business hours know to expect response the following day.

Next steps, beyond a pilot, this could lead into some pre-qualification questions that ask the customer for some specific information so when they reach the sales or support teams the basics have already been covered and you can start to reduce your resolution times. It’s an opportunity to find out more about your customer.

Step 3: Enriching the conversation

As well as being able to leverage NLP (Natural Language Processing) a conversational AI has tools like sentiment analysis and entity extraction to enrich conversations with additional metadata. From the initial enquiry you can pull the sentiment to give your teams a quick reference about the happiness of the customer before the conversation even begins. With entity extraction pulling out people, organisation, places, dates and time along with keywords your team can gain a clearer understanding about what the enquiry is about faster.

Next steps, with analysis in place there’s the option to escalate customers with a high negative sentiment and start to identify trends through the entities extracted.

Running a pilot can be an effective way to trial a new capability in your business when it is paired with measurable KPIs to assess the effectiveness. The quick wins build a solid foundation to improve CX across the business and a path to rolling out the improvements to production.

Conversational AI will improve conversations in real-time with customers to enable a dramatically better CX. Qualify leads faster for sales, improve resolution times across support enquiries through pre-qualification and enrichment data and provide a better experience to improve customer satisfaction.

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Pattr brings you closer to your customers.

A conversational AI SaaS platform to power, enable, enrich and understand conversations between you and your customers, in real-time and at scale.
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