Investing in data & tech to understand your customers can lead to your organisation becoming less customer centric!
Wait, what?
Innovation is important for any leader; it guarantees the sustainability of your company. Customer centricity is often the basis for this innovation. To achieve it, many leaders invest in expensive data tooling. From our experience in the field we have been able to pinpoint the following signs that prove it doesn’t work:
- There are no resulting innovations and, at the same time, no improvement in customer satisfaction KPI’s.
- Yet there are more dashboards showing a variety of versions of the truth, creating more work.
- A frustration develops through each layer of the organisation, resulting in poor employee retention.
This video, where Tricia Wang speaks at a Google event, confirms many of the experiences that we have gained in the field:
The bigger picture
Customer centricity has been a household term in ‘product country’ for years. It has many interpretations, here’s ours: A team builds a product and/or service that meets customer expectations. They also anticipate changes in these expectations. For this reason, satisfied customers continue to return and become advocates for the quality of the brand. It may seem over simplified, but it’s a good starting point.
Now, let’s talk about a major misconception when referring to customer centric product development.
“Almost all the executives that we work with are convinced that they are customer centric. But they are not!”
When we take a dive into their data, we realise that they aren’t actually achieving their intended results. Their innovations aren’t catching on, and their customers are gradually losing faith in their core business. Not great to hear, but someone has to be honest.
How did this happen?
Everyone’s talking about data driven product development. This means that most organisations are quantitatively (big)data driven: they collect a ton of data, which is then stored in huge data lakes. They have invested a lot in expensive tooling to magically transform this data into insights. As a result, they expect to become more innovative, be able to make better decisions and react more efficiently to changes in the market. When they realise that they’re not yet reaching their targets, they throw even more capital in to tooling. And this is where it becomes a vicious cycle. It’s just not how things work.
Use of big data is meerley a fraction of what it means to be customer centric.
“Adding more and more tooling often results in poor quality insights.”
You often end up with more dashboards showing various versions of the truth. This results in frustration, leading to low employee retention and customer satisfaction KPI’s that never improve.
What to do now
We understand how you’re feeling, believe us. But hold off on throwing out all your data and tooling just yet. It can all still be a worthwhile investment. Use it wisely, and you have a great tool for developing your business and extracting the information you need. In time it can increase your customer centricity and in turn hold on to your customers and team.
“First things first: go back to the basics!”
Focus on the following aspects:
1. Taking care of winning teams
Your people are your number 1 superpower. Make sure they’re equipped with a full arsenal of the skills they need to achieve and sustain customer satisfaction. In a data driven world, it’s your humans who need to feel empowered.
2. Curating a customer focused culture
The culture of a company begins with its leaders. It can be difficult to measure but if you are not customer centric yourself, as a leader, be brave enough to acknowledge it. Changing the focus to your customers builds the base for your teams aspirations, and gives them the ability to adapt according to the changing needs of your customers. Suggestion: set some time aside each month to meet with at least two of your customers. Their feedback will be invaluable to your team and future innovations. Not convinced? Look at it this way: “The people whose decisions impact the customers the MOST are the ones who interact with the customers the LEAST.” (Matt LeMay)
3. Asking the right questions first
Then get to work with the right data: Questions often get asked from a business perspective. For example, in the media world, ‘how can we sell more VOD subscriptions in southern Europe?’ or ‘How can we increase the margins of B2B ads?’. These questions are recognisable due to their use of jargon, and often refer to internal goals/KPI’s.
However, it’s the customer who has a problem and not the technology. So it’s better to start with a question from the clients perspective. These questions focus more on understanding the needs of the customer and have nothing to do with company goals/KPI’s. ‘How do people in southern Europe consume their entertainment?’ and ‘How do prospects determine the worth of ads?’.
Big data gives an indication of where to find the problem. Qualitative (thick)data tells you why the client is experiencing problems with something. Both are useful for various outcomes. Take a look at the below diagram. In short: with big data you optimise your current product and/or service in a known environment. And with thick data you innovate new products and/or services in an unfamiliar environment. Interested? You can read more about this here.
Integrated Data Thinking™ is a framework developed by Sudden Compass®
4. Take it easy on the dashboards
There is such a thing as too many dashboards. Keep it simple. Take it easy on the dashboards. There is such a thing as too many dashboards. Try to keep them to a minimum and keep it simple. How we do it:
a) Ensure a common ground regarding definitions and data sources to prevent misalignment due differences in interpretation of the basic definition.
b) Do not only build scoreboards of the goals (for example: number of VOD subscriptions). Rather focus on the actions which influence the number of subscriptions (returning visitors, time spend, usage of features, etc). These dashboards show you the positive and negative impact of changes way ahead before you notice the impact on your desired goals. This gives you the time to adapt.
Innovation is important for the future of your organisation. Don’t give up, keep improving. Start with the basics before you make any more major changes in your data and tech.
Still having issues with getting improvements out of your big data? Maybe you have skipped a data maturity level and this article can help.
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