Reducing conversational AI project risk: Step 2
Innovative, cutting-edge, ground-breaking – these are all words used regularly to describe conversational AI technologies. Being the organisation that deploys an innovative technology typically requires being comfortable with a high level of risk. However, most companies don’t have the financial flexibility or company culture to take that degree of risk, whether real or inferred.
Deploying conversational AI solutions like chatbots and virtual agents can be risky but doesn’t have to be. You don’t need to be an early adopter of innovations to benefit from the technology. These solutions have been used by businesses for over two decades as part of their customer engagement and employee experience strategies, and you can take advantage of those learnings to deploy reliable, successful projects.
In this three-part blog series, I’m sharing three steps for achieving conversational AI success while minimising the risk for your organisation. Last time, we delved into Step 1: Be selective when deciding on a vendor and technology. If you missed that post, I recommend you read it first before moving on to the second step:
Step 2: Build a business case with realistic goals.
Embarking on any business project without identifying the goal is always a risk, so it is essential that you have a realistic business case and clear objectives for your conversational AI project. An experienced vendor will be able to assist you with this process by performing a textual analysis of your existing data, such as live chat or contact centre transcripts, to identify what queries can and should be automated with conversational AI.
Starting with this analysis immediately reduces risk because your business case is being built around your own data. It’s combining the vendor’s expertise directly with the information that is unique to your customers, employees, and company. Instead of guessing your users’ self-service needs or taking a generic approach, your business case is customised to you and your pain points from the start.
Follow that initial analysis with a consultation workshop to review the results and collaborate with the vendor to identify your key performance indicators (KPIs) and set realistic goals. These business objectives will directly inform how your chatbot or virtual agent is built and implemented. Having clear goals and deciding how you will track progress and measure outcomes minimises the danger of investing in a project that won’t really meet your needs.
The key in this step is to build your conversational AI business case around realistic and obtainable goals. Being practical about what you are automating and setting sensible targets for your solution creates a solid foundation for your project. It keeps your investment focused on reliable, reproducible outcomes and business benefits.
In the third and final instalment of this series, we will talk about starting your conversational AI project with a pilot and the best approach to minimise risk while rolling out a full deployment. A great resource for better understanding the financial investment needed for a successful virtual agent or chatbot is the Guide to Enterprise Conversational AI Pricing: Calculating the Cost of a Successful Chatbot or Virtual Agent. Even if your company isn’t at the enterprise-level, this guide provides valuable insights into budgeting and calculating ROI that’s useful for all organisations.
This post originally appeared on the Creative Virtual blog.
Mandy joined the Creative Virtual team in 2008 and currently manages the company's marketing activities. She is a member of the Forbes Communication Council, was named to the Women Leaders of Conversational AI, Class of 2023, and has won multiple awards for driving brand recognition, thought leadership, and lead generation activities. Mandy...
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