Published January 18, 2023
Client intelligence is a key pillar of client success. A data-driven approach to understanding your clients, it can make all the difference when growing your business.
In this article, we’ll look at:
Client intelligence is the process of understanding and predicting customer behaviour based on a large data set. Using advanced software to collect and analyse this data, businesses can identify patterns and then act on them to improve customer satisfaction and gain a commercial advantage.
Great service is central to client success, but it’s hard to provide superior service if you don’t understand what your clients need. Client intelligence is all about developing that understanding.
Once you start looking, you’ll often find that the data you need already exists. Clients share information all the time. Some of this comes directly when they tell you who they are and what their needs are. Some of it is less direct but still deliberate, such as activity on social media or, for B2B clients, the way they present their own businesses. Some of it comes incidentally, through the patterns in their behaviour, such as how they use your services and how often they interact with you for support.
This data can be broken down in a number of different ways, to help you in thinking about it. One way is to split it into reference data and transaction data. Reference data is basic information about clients: who they are, what they want, and what their preferences are. Transaction data is records of how they interact with you. It tells you about their relationship with your company and products.
Another division is internal and external sources of data.
Internal data is information held by your company, such as client files and call or meeting records. It’s the natural starting place for client intelligence analysis, as it’s readily available and clearly relevant. A lot of this data gathers in your company through regular record-keeping, especially in CRM systems. But it might be actively acquired for the purpose of client intelligence analysis, for example through surveys and feedback forms.
External sources of data are also important. This is data from outside your company that will shed light on your clients. It can include clients’ financial reports, social media profiles, and marketing materials. It might include contextual data, such as market trends.
Although this information can be valuable, as pure data, it doesn’t achieve anything. It’s when it’s analysed and conclusions are drawn that you develop an understanding of client demands, motivations, and actions, an understanding that you can use. This is client intelligence.
Client intelligence is important because of the way its insights can be used. It informs decisions about marketing, product development, and other strategic initiatives, leading to better decisions and greater success with clients.
When done well, client intelligence provides a detailed view of who your clients are and how you interact with them. This extends beyond an overview into understanding different segments, or even individual high-value clients. The data can then be used to improve client success in a number of ways:
The better you understand your clients, the better you’ll be at providing them with the relevant product or service. Client intelligence can tell you what products and features will suit your clients, and often can provide this information better than the clients themselves can.
This is partly about the products you already have. An improved understanding of your clients will help you identify which products are most suitable for them, how to pitch those products, and how to adjust them to client needs.
It’s also about developing new products. Once you identify client needs, you can adapt existing products or create new ones to meet those needs, safe in the knowledge that there is a genuine need for them.
As well as improving your approach to products, client intelligence can improve your approach to client service. Data can show you which processes and practices work well and which ones are not effective, what constitutes good service and how you can achieve it.
91% of consumers are more likely to shop with companies that personalise their offers and recommendations, and the same psychology is relevant with the representatives of client businesses. Good service and personalisation make clients feel valued and appreciated, which dramatically increases the likelihood that they will continue working with your business.
Client intelligence can provide a significant boost to sales, by allowing you to work smarter.
Part of this stems from the points we’ve already addressed. If you have better products and better service then you’re more likely to earn recommendations and will be in a position to prove your value to new clients.
But it’s also about the marketing and sales campaigns themselves. Client intelligence can provide valuable data on the types of campaigns which have been successful with these clients in the past, as well as how, when, and where the best opportunities to reach them will be. It can directly shape your pitch.
This extends to market segmentation. Data analysis can identify the groups of potential clients most likely to be interested in different products or open to different offerings. By profiling those market segments and identifying potential clients within them, you can personalise your approach and put your sales effort where it will have the greatest impact.
All of this will help bring new clients your way and please the ones you already have. This helps you build up a client base, but how can you make sure that you sustain it?
The answer lies in analysing client churn, the rate at which clients stop using your services. Client analysis can show you patterns in this, including which clients are most likely to leave, when this happens, and what the warning signs are that you’re about to lose them. Using this analysis, you can intervene at the critical moment to keep clients on board and reduce churn.
The insights that come from client intelligence aren’t just useful on a tactical level, in finding ways to handle clients and fulfil their immediate needs. They can also be useful in developing the right strategy for your business.
Client intelligence provides important insight into the broader population you draw your clients from and what’s happening in your market. You can get an understanding of how clients are behaving, which products are working well, and what unmet needs there are. You can then use this to develop a forward-looking strategy, one that leans into these patterns and seizes opportunities which your competitors may have missed.
As with any tool, there’s a risk of over-hyping client intelligence if we only talk about the benefits. But this is a relatively new technique using new technology, and there are some limitations to be aware of.
Client intelligence is grounded in pattern-seeking software. This software is incredibly powerful, capable of processing volumes of data in seconds that a human would need years to analyse and of noticing subtle or complex patterns that are hard to spot.
The downside of this is that the software may misrepresent this data. It can provide false positives or miss real patterns that don’t fit its parameters. Humans are far better at recognising patterns once they’re put in front of us; even a toddler can reliably identify a picture of a dog, while the most sophisticated image analysis software would struggle. Humans are also capable of identifying biases and limitations in the data they’ve been presented with, while software can only work with that data.
A human touch is therefore needed to add a layer of analysis and interpretation. Client intelligence provides high-volume analysis, which humans can refine.
There’s another layer of analysis that client intelligence software can never provide on its own, and that ensures the need for human insight. That layer is understanding.
Client intelligence software is good at finding patterns, but it can’t work out why they exist. To use the language of statistics, it can spot correlation but not causation. Given the right data, a computer could tell you that high temperatures and high ice cream sales happen on the same days, but not what the connection is. It takes a human mind to understand that people are buying ice creams to cool down. The same inability to provide explanations exists with client data.
This understanding is vital to working out which patterns matter. Over the decades, there’s been a correlation between sales of mozzarella cheese and the number of engineering graduates in the United States, with the two rising in a similar pattern. Are the two related? Almost certainly not, but a computer can’t tell you that, any more than it can identify meaningless from meaningful patterns in client data.
Once again, the touch of a human expert is needed. Without it, there’s a risk of treating every correlation as significant and misunderstanding the connections.
But while humans are needed to overcome the limitations of client intelligence software, they also provide a limitation.
Most people don’t understand how client intelligence software works, either in the detail of its coding or in terms of what it produces. This can lead to mistrust and an unwillingness to rely on the results. It can also lead to the opposite problem of excessive trust, where people take the outputs at face value just because the technology produced them.
To make effective use of client intelligence, you have to educate employees about its uses and limitations, so that they can understand, trust, and appropriately use the insights.
Technology is never a magic bullet. It’s one more tool and its value depends on the people using it.
All of this leads to an important question: if client intelligence has so much potential as a tool, then how can we use that tool better?
In an increasingly fast-paced world, speed matters.
It’s easier to capture data as it happens than to go back and find it later, so set systems up to collect that data automatically or as a small step in the work people are already doing. For example, it only takes a few seconds for client service managers to add relevant tags to call recordings as they’re made, and these tags can create huge opportunities for analysis and insight.
Once you’ve done your analysis, act quickly on it. Swift feedback lets people make quick adjustments to their working practices and so gain the most benefit. Acting quickly on analysis will make your business more responsive and flexible than your competitors, giving you an edge.
Working broadly, both in the data you use and in how you do it, will give you better insights.
Look at a wide range of data sources, both internal and external, reference and transaction. Consider the full breadth of information you have access to, such as product usage data, sales stats, and client feedback.
When using the data, carry out your analysis along a range of different axes to provide different insights. This can include approaches such as segmenting current clients to understand the groups you serve, or looking at patterns in client behaviour over time, to understand how your base is changing. Look forward as well as back, exploring where patterns would go if allowed to continue.
In all of this, make use of the human elements. Technology-based client intelligence is processed material, not an end product, and you need to include intelligent human analysis to refine it and add understanding. But you also need to ensure that the employees you share these insights with understand where the information comes from, so that they can have faith in it while recognising its limitations.
In the future, client intelligence will become increasingly important for CS teams, for a number of reasons.
One reason is the growing volume of data that’s available. Technology is becoming increasingly effective in capturing information and people are increasingly willing to share it. The growing number of digital interactions we perform every day adds to this data trail. The systems used by companies contain more and more data over time, which means that there’s more to work with.
What can be done with this data is also becoming increasingly sophisticated. More advanced software is better able to analyse and interrogate pools of data, to draw patterns and conclusions from them. And with more experience, the human tools, our understanding and analysis, are also becoming more sophisticated. This means that client intelligence can provide increasingly powerful insights.
Artificial intelligence is likely to play a key role in this. AI software is becoming more effective. It can learn and adapt at an ever-increasing pace, and process data far faster than a human could. While there are insights and leaps of logic that humans can make but AI can’t, patterns we see that it would miss, that gap is shrinking by the year. The limits of client intelligence are receding.
And ultimately, client intelligence will become more powerful because teams will get better at acting on it. The more experienced and confident staff become in instructing client intelligence systems, interpreting their results, and providing quality service based on them, the better. Client intelligence won’t just become more powerful because of improved software; it will also be because the humans around it build fresh insights upon those of the past.
With the growth of data and the rise of artificial intelligence, client intelligence will help CS teams to better understand their clients and help manage, retain and grow clients, cementing the place of client intelligence as a key business tool.
In any business, you have to make constant decisions about client needs and the best way to provide a solution for those needs. Client intelligence helps you make informed decisions, grounded in facts and data. It has its limitations and needs careful use to get the best results, but it can lead to better outcomes for you and for your clients. And as client intelligence becomes more powerful, these outcomes will drive more successful client relationships.