A retailer decides to hire a small army of extra employees because, based on what was sold the same time last year, there is reason to believe holiday shoppers will be coming to the store en masse.
A health and wellness company looks at the feedback coming in through a chatbot it uses for customer support and introduces a mobile app to help customers keep track of their fitness levels.
A travel firm removes two out of the three steps that were previously required to complete an online booking because, thanks to tools that show how its web site is used, that’s clearly what customers want.
These are all examples of data-driven decisions. In the most successful companies, they are not simply isolated incidents. They speak to a consistent approach taken across sales, marketing, customer service and other business functions. It is a mark of a data culture – where an organization prioritizes data as a key input into business strategy.
According to a report from consulting firm McKinsey, 15 to 25 per cent of EBITDA increases owe
their financial performance to the data culture they’ve developed. That’s because data allows companies to accelerate:
Efficiency: Data can be used to identify processes that are slowing employees down, or creating friction in customer experiences.
Productivity: When data is close at hand, team members can find answers to common
questions more quickly, and make faster progress on solving critical business problems.
Innovation: Data doesn’t just give a window into what happened in a business and the market it serves. It can also indicate where customers have unmet needs, which can help inform the design of new products, processes and experiences.
For many Canadian businesses, the problem is not a lack of data. It’s trying to effectively collect, manage, analyze and report on the right data. It becomes part of the culture when everyone – no matter the functional area in which they work – can act upon to further business objectives.
A good way to begin developing a data culture is to envision the impact of data-driven decision-making across the disparate stakeholders that make up a typical company. Some of the most common examples are as follows:
Reps used to rely a lot on their memories of previous deals to win more customers. This can work when you’re dealing with a small account base, but data becomes transformative as you scale.
By using a CRM, for instance, reps can share what they learn about customers in a centralized system that shows the most likely way to close more deals. This data could include customers’ most common objections (and how to overcome them), products and services that are trending in popularity and even what kind of bundles or configurations of products and services resonate most.
CMOs often have great instincts for what makes for compelling ad creative, but data provides an additional layer of knowledge to deliver even stronger campaign results.
Think about how artificial intelligence could assess the likelihood of customers to click on a digital or social ad, for instance. CMOs and their teams could then use marketing automation to A/B test different versions of the same add, social post or e-mail subject line.
Agents might be great at troubleshooting product issues, but their jobs become harder than they should be when they’re spending too much time scrambling for the right information.
Most of us have probably experienced situations where we’ve reached out to a company for help and have had to repeat the same purchase details (or even our names) over and over. Data-driven service takes all that unnecessary detective work away from agents, allowing them to focus no what they do best.
The most valuable data in any organization is really customer data, because it allows a company to take those relationships further than they’ve ever gone before.
A data culture will ensure, for instance, that customers aren’t greeted generally when they log into their account, but with their name and pointers to what they might need based on previous interactions. It will solidify best practices such as only reaching out to customers through the digital channels they prefer (such as e-mail or text message instead of phone calls) and will provide promotions that reflect their purchase histories.
Smart companies will also develop a data culture with an eye to improving employee experiences. Everyone on the team, no matter their role, should know where to find critical sources of information. They should be well trained in how to share data with other departments and ensure silos don’t get in the way of best serving customers. A data culture will also encourage employees to measure everything they’re doing in order to continuously improve their performance.
How do you sustain a data culture over time? By committing to it over the long term.
Data needs to be treated as a source of value – not just by those on the front lines but those in senior leadership roles too.
Investing in technologies that make it easy to visualize and make use of data also fuel the culture, because employees feel empowered and motivated to tackle bigger challenges.
Data ultimately becomes associated with a company’s culture when you can tell stories about it. This isn’t limited to the way your business used data to avoid risks or make more money. Share stories about how the people all over your organization tapped into the power of data to redefine what excellence in their role looks like, and how the company achieves success.
You might not use the term data culture very often within your business. If you’ve put in the effort to develop one, you probably won’t need to – the link between data and the way your company operates will be obvious to all.