It is obvious to most that knowledge is better than assumptions. Especially when it comes to strengthening one’s market position. So analysis and data are rarely in short supply. Unfortunately, many analyses end their otherwise hopeful lives in drawers and on shelves. And ultimately in the “small flammables” department. Why? Because many analytics fail to provide the answers that management, sales, finance, marketing, and product development are looking for to improve the company’s position, top line and bottom line.
This is very often due to one or more of the following:
- Static answers are given that cannot be used in the future. Analyses and data focus on consequences of what the company has done. That is, (1) they are already historical and (2) unable to tell why customers reacted as they did. If the analysis is to look only at consequences, such as “How many people know the company? How many consider the company? What is the distribution today between high, medium and low frequency customers?”, then this form is a good tool. However – analyzes like these cannot provide answers to what the company should do (services, products, and behaviors) and communicate (key message, endorsement, style, and tone) to bring about change, e.g., “Get more people to consider the company. Convert low-frequency to medium-frequency customers”. In other words, the analyzes and data collected are static, and therefore often end up on the back shelf as soon as they are reviewed – because they cannot lead to directions for improvement.
- You’re asking the wrong thing. Analyzes to identify improvements in company products, market offerings and communications often focus on asking “what do customers want?” rather than “what problems are you, the customer, trying to solve?” But why is this the wrong approach? Most importantly, it is wrong because customers can only relate to what they already know. If Henry Ford had asked the Americans of the day what they wanted most – they would probably have answered “a faster horse” or something similar. That would never have led to the invention of the car. And if Steve Jobs had asked the first music-loving digital natives what they wanted, they would probably have answered “a better audio format than MP3”. It would never have led to iTunes, which revolutionized the way we could organize music – and at the same time solved the music industry’s dilemma of monetizing single tracks, especially old ones that were gathering dust.
- There is a lack of coherence between analyzes. It is rarely the lack of analysis and data that leads to poor or inadequate use of the results. Instead, there is often a lack of coherence between the many analyses and data produced by, for example, marketing (awareness, qualified awareness, consideration, brand image, campaign metrics) and sales (customer satisfaction, customer distribution). Not only content, but also something as impractical as platforms can create complexity and therefore confusion in the large amount of data collected. So, for example, actions in sales to reinforce the customer experience of “it should be easy to be a customer because X” are not included in future brand measurements of marketing because the two departments’ systems are on different platforms. When the link between what drives business and how customers respond to the company’s offerings and services is not optimized, it is difficult to impossible to identify the most optimal actions for improvement. Result? The company archives its analyzes, claiming they didn’t provide relevant answers anyway.
At Clienti, we have a clear recommendation for you, and we are happy to help and advise you when it comes to analysis:
1. What really drives business? Start with qualitative analysis based on “what problems do customers want solved? And how do they measure the solutions?”. Identify customer personas, based on needs (rather than age, gender, etc.). Quantify these, so you know which needs and issues you as a company solve better than any other provider. These are the parameters you need to analyze further. Qualitative methods can be focus groups, in-depth interviews or observations. These are followed by quantitative analysis, for example through panels or other online analysis.
2. How are you perceived by customers – potentials and existing? And how do they rate your solutions? Get quantitative clarity on where you stand in relation to customers? If your company is particularly focused on how you serve customers in terms of customer service, complaint handling, pre-purchase advice, etc., ask your customers – potential and existing – how you are perceived on these parameters. Not about everything else. Methods can be online analysis with potential and existing customers.
3. Make connections between customers, customer personas and sales. Ultimately, analysis and data collection of what drives business, customer experience of company offerings and services should lead to sales. And preferably more valuable sales – that is, you are able to sell more, at a better price, more often – and to more people. So make the connection between the customer personas you’ve identified and their value to the business. It starts with enriching your customer data with which persona(s) best describe the customer. Then make sure everything the company does for the customer is tracked – newsletters (what content generates activity?), sales, follow-up, complaints, etc. This ultimately creates the overview you need to answer “what do we need to do and communicate to improve our position, our services and ultimately our sales to the customer?”.