10 Actionable Tips to Optimize Your Customer Intelligence (CI) Strategy

10 Tips to Optimize Your Customer Intelligence Strategy

If you want your business to succeed, you need to understand your customers better. That means you must have an effective customer intelligence (CI) strategy in place.

What’s the best way to think about customer intelligence? How to derive actionable insights with customer data? And how can you improve your customer intelligence strategy?

What Is Customer Intelligence (CI)?

Customer intelligence is a subset of business intelligence. It refers to the process of both gathering and analyzing data about your target customers so you can better understand them, create unique customer profiles and market to them more effectively, and serve them with greater efficiency to effectively increase customer loyalty.

The ideal end result is that you create a competitive advantage, make better business decisions, improve your customer relationships, and ultimately make your company more powerful and sustainable.

The data you gather on your customers may come in many forms. You’ll want to understand who your target audience is (including their demographics, their values, and their perspectives), how they behave, and how they interact with your brand.

It’s a substantial task to collect all this information, especially given the sheer number and complexity of data-related technological tools available for attaining predictive customer insights. But if you want to remain competitive, this is a task you have to tackle.

Tips for Optimizing Your Customer Intelligence (CI) Strategy

These are some of the most effective tactics for optimizing your customer intelligence strategy:

1. Choose the right tools. It’s impossible to gather and analyze all the data manually that you need to understand your customers. You should seek sophisticated AI-driven technological tools to help you do this: tools that empower you to monitor a greater number of customers in more detail, and streamline the process of organizing and studying the data you collect with machine learning.

There are thousands of AI-powered business intelligence and customer intelligence software that can help you do this, but not all of them will be relevant for your business, and not all of them are going to be equally powerful. It’s vital to make these decisions seriously, evaluate an array of potential tools, and select only the best ones to suit your needs. Once you have the right tools in place, all the elements of your customer intelligence strategy will become easier.

2. Create a comprehensive strategy. Next, create a comprehensive strategy and document it. Too often, businesses attempt to improvise with customer intelligence: gathering information on their clients with no concrete agenda and no priorities to dictate their data-management approach.
At best, this will be a waste of your time; at worst, it will negate the benefits you hope to gain from customer intelligence. Start with a foundational strategy and work from there.

3. Unify and centralize your data streams. One of the greatest challenges in customer intelligence is finding a way to unify your data streams. You’ll gather information on your customers across a number of channels and possibly through many different departments.

How can you make sure these data points are in agreement with one another? How can you make sure that decision-makers have access to all the appropriate data? For most firms, the goal is to centralize all your data, and create a single source of truth and a convenient access point for decision-makers.

4. Coordinate departmental efforts. Remember, customer intelligence isn’t the responsibility of just one department. It’s a duty of all your departments, including sales, marketing, customer service, R&D, and even administration.

If you want to see the best results, you need to make sure people in all of your divisions follow the same directives, share data when necessary, and collaborate to achieve the same goals.

5. Use the context of the customer journey. Map out and fully grasp your customers’ journey. How do people first hear about your brand, how do they form relationships with it, and what do their ongoing exchanges look like?

The data you gather will be much more relevant and easier to apply if you understand it within the context of the customer journey. At what point in the journey is this data most applicable?

Don’t neglect real-time analytics

6. Don’t neglect real-time analytics. Real-time data analytics are easy to neglect, but they’re incredibly valuable as a resource for understanding customer behavior. What are the traffic patterns of the people visiting your website?

How are they browsing your physical establishments? How do your metrics ebb and flow throughout a day or across the week? These insights are difficult to glean from traditional data streams alone.

7. Segment your customers by behavior (and other factors). Studying party data in the aggregate is effective, but it’s even more constructive to study information at the more individual customer level. In other words, it’s worthwhile to segment your customers by behavior as well as other factors. Collectively, your clients may behave in one way, but how do your most excitable customers behave? What about your most cautious ones?

8. Focus on CX metrics. Customer experience (CX) means everything for your business. If your customers have consistently positive experiences from the time they first hear about your brand, they’re going to keep buying from you and potentially evangelize on behalf of your operation. That’s why so much of your customer intelligence strategy should focus on customer experience metrics, for example net promoter score (NPS) and customer lifetime value (CLV).

9. Let the data lead you to new conclusions. Confirmation bias frequently guides people to form conclusions, then perceive only the data that supports those conclusions. To form more objective, reliable insights, you need to do the opposite: Start from a neutral mindset, and let the data lead you wherever it may go, which may sometimes entail new conclusions.

10. Keep optimizing. Finally, try to keep optimizing your customer intelligence strategy. There will always be new tools to test, new experiments to conduct, and new processes and systems to integrate. Stay adaptable if you want to keep learning and improving.

Do you want to understand and serve your customers better? You have to have the right technological tools to help you do it.

Aisera’s AI Customer Intelligence platform provides proactive, predictive, and prescriptive auto-resolution of tasks, requests, and actions relevant to your customers. Sign up for a demo today!

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