Navigating AI-Infused Customer Analytics: 7 Steps to Boost Success

Are you ready to successfully get started with data-driven working? These seven steps will help you get going.  

1. Define your goal

What exactly do you want to accomplish? Achieve growth with the same number of sales people? Sell more of a particular product? Double the average revenue per customer in three years?   

2. Collect data

As already mentioned, it’s likely you’ve already got ample data, for example in your CRM system. But it can also be useful to monitor the mood of your customers on social media. Don’t forget operational data too, such as logistics or inventory data. Keep an eye on data quality, though. Data does not have to be perfect, but it should always be fit for purpose. Remember: garbage in, garbage out.  

3. Analyse

Feed your data to models that analyse your customers. These can determine for you who your most valuable customers are, which ones are ‘sleeping’ and which ones are definitely in danger of being lost. Models that can predict demand or recommend products are also extremely useful.   

4. Take action  

Send your most active customers a gift, activate dormant customers with a discount code, send newsletters, interact on social media to influence the mood, adjust your porfolio and design business processes more efficiently. Call customers who are just about to make a repeat purchase and make them an irresistible offer. All this sounds great – but how do you choose which action to take? Account managers, marketers and customer service staff can determine this easily with the insights provided by AI-Infused Customer Analytics dashboards.  

5. Work with the right people

To get the most out of a modern data platform, you need a multidisciplinary team, with many different specialisms and experiences. When there are multiple perspectives and people learn from each other, it usually produces better results. Developers often think from a technological perspective, while marketers, sales people and project managers focus on customer needs. You also need engineers to create a data platform and people who understand business intelligence to create dashboards. All this is specialist work that should not be underestimated. If you don’t have that knowledge in-house, consider using an IT partner.     

6. Include every employee  

Involve the entire organisation in the change brought about by working with a modern data platform. This increases support and helps you prioritise. Employees who have contact with customers are the best source of information when it comes to discovering where the biggest opportunities for improvement lie. Perhaps you can make their work more enjoyable, for example, by automating repetitive work. It’s also important to train your employees: they need to learn how to work with data, understand the dashboards and be aware of what actions they can take based on the scores provided by the algorithm.  

7. Start small

Many organisations underestimate the value of their data, mistakenly thinking they are not yet ready for AI-Infused Customer Analytics. One reason for this is that they assume that data needs to be 100% complete and perfect. They might also assume that organisations, systems and business processes must first change dramatically. However, you can get quick results by starting with even a small use case. You can use the experience gained from this for larger-scale follow-up projects.  

Want to know more about AI-Infused Customer Analytics? Need some help? Contact us for a friendly chat.