Creating a framework to support AI integration

In this video we will look at how to build an AI-driven framework inside an organisation. We also delve into what the key performance indicators are that allow us to track improvement and how we can monitor these. There are four key elements that set a good foundation for an AI-driven approach to customer experience. As discussed in the previous article, the first is to ensure that exposure to AI is not confined to only a few individuals on your team. To really integrate this approach, you should have a task force across all departments that can work together to embed AI-driven practices throughout the business.

Once you have established this, it is important to understand how customers interact with the brand by mapping their entire journey, including all the key touch points. You also need to know what practices are currently in place that measure the customer experience so you can identify where there are gaps to be filled. You will want to establish where you can use AI to understand and improve these interactions. The key is not to implement too many things at once but to have a clear roadmap to test, learn and continue to enhance, all with a timeline that is achievable dependent on your budget and resources.

When you are looking to map the customer journey, it is important to start with a framework that ensures you cover all the key inputs required to get a full picture of the multiple ways that consumers interact with your brand.

The first step is to understand the stages a customer might typically go through. You’ll consider how they get to know about your brand and thus interact with it, how they behave and where they go when thinking about buying. Look at how they transact with you and how you interact with them after they have purchased. Also consider any other touch points on their path to purchase. You must also look at the types of customers that typically buy from you. Can you define their personas? For example, how old are they, what are their interests, are they male or female , young or old. This information will help to understand if different customer groups have different journeys or experiences that also require mapping.

Finally, think through how you market to potential customers at each stage, how they feel, what may be pain points and potential opportunities. At this stage you don’t need to think about AI but should put a focus on mapping the experience in as much detail as you can.

Once you have a clear idea of the customer journey, the next step is to understand how you capture information and measure performance. This includes the data sources and technology used and who manages each phase. It is also important to understand how you measure success in terms of key performance indicators and whether you have an experience scoring method in place.

After this you can start considering which AI methods would be useful to enhance the information you capture. Look back at the AI techniques and tools discussed in Activity Two and Three to help define this. It is important that this process is completed with the cross-department task force and everyone agrees with the final framework, including where AI can help.

When you work towards developing this framework you also need to look at how you plan on measuring success. The key performance indicators to measure success may not change from what you had before. For example, increased searches and awareness for your brand, higher engagement with the website, more sales and repeat customers, and increasingly positive feedback. AI-driven techniques such as text analysis or personalisation will provide a means to obtain richer customer information across all these KPIs. You should compare the same metrics before and after implementing changes that are driven by AI initiatives.

With a customer journey map and a measurement framework in place you can make key decisions about which platforms to use and what AI methods to prioritise. Building a roadmap of how you want to evolve your AI initiatives will assist in planning a program with a test-and-learn approach. It will also mean that you can work towards tangible goals to achieve success.