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The data you have may not be the data you need...

Digital Growth
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Having all your data ready to go without any clear objectives in mind is kind of like walking around with a hammer looking for a nail to hit into the wall. Aside from making for a terrible episode of DIY SOS, it’s also likely to lead to a failed project where nothing is actually solved. In other words, it’s far from the most logical approach - so put the hammer down, Nick Knowles.

Yet this misconception is more common than you might think. 

You build up so much data that can support decision making within your business, but knowing that this data could be valuable is only half the battle. Without being 100% sure of how it’s valuable, you’re likely to fall into the trap of just using what you have, rather than identifying what you actually need. 

This is counter-productive at best…and that’s us putting it nicely!

Trying to identify a use for your existing data is not the ideal flow - in fact, it’s pretty much the reverse of the most effective approach. The primary focus should always be on what you want to know, why you want to know it, and what this achieves

This makes setting objectives and goals for your project an absolute non-negotiable, and data shouldn’t even be a consideration until you do. After all, why limit yourself by allowing restrictive data to dictate what you’re able to achieve? 

Only once your objectives have been set in stone can you begin working out how you’ll accomplish them, and it’s at this point you can start diving into your data. But much like a Brit abroad, try not to just stick to what you know (did you really fly all that way to have gammon and chips for dinner?). 

To ensure a purposeful approach, you should always start by identifying what data is required, and follow this with an audit of what data is currently available. This provides you with a comprehensive overview of the next stage.  

What exactly this next stage looks like depends on the missing data sets you identify. Your data collection could lead you to expanding or refining existing data collection processes, for example, or even looking at third party sources. 

Wherever you end up, you must approach every project understanding that the data you have right now may not be the data you need. And just as importantly, you must be prepared to do something about it should you want to accomplish the goals you’ve set out to achieve. 

As IBM’s Institute for Business Value put it, “the most effective data strategies identify business requirements first, and then tailor the infrastructure, data sources and analytics to support the business opportunity.”

Now we know what you’re thinking: that’s easier said than done, right? 

From sales, marketing, and customer data to financial, administrative, and even email data, you’ll find that your business likely has an array of sources already at its disposal - and this means that there’s already a whole lot of data to consider. 

But the efforts are always worth the reward, with almost two-thirds of digital leaders believing that data and analytics will be the top technologies to deliver competitive advantage in 2024. Moreso, with a staggering 98% of executives agreeing that it is somewhat or very important to increase data analysis by their organisations in the next one to three years, not taking the right approach to your data could see your business getting left behind in its industry. 

So what does the right approach actually look like? Let’s delve into an example.

Example: Ecommerce Retailer Case Study

Consider an ecommerce retailer that wants to increase its sales because, um, what e-commerce retailer doesn’t want to increase its sales?!

Initially, the team is eager to analyse the customer data they have to hand in order to identify trends and make the necessary improvements to skyrocket sales. However, in doing so they make a common faux pas that undermines their efforts and prevents them from successfully achieving their objective.

Any guesses? That’s right - they’ve focused on what the data they already have can show them, rather than first defining clear goals. Rookie mistake

So, what should the team at this ecommerce retailer have done differently? At the risk of sounding like Carol Vorderman (or Rachel Riley for the finite number of under-30 Countdown fans amongst you), here’s how you could’ve done it…

Step 1: Setting the goal

The team convenes to discuss and set precise goals for the project that align with the overall North Star KPI they work towards. Linking back to their North Star metric focused on spurring customer growth, the team determines that their primary objective is to increase sales by 20% over the next quarter, and also set secondary objectives that include improving customer satisfaction and reducing cart abandonment rates.

Step 2: Identifying and auditing the data

Keeping their objectives at the forefront of their approach, the team identifies that they need data on customer buying patterns, feedback on user experience, and cart abandonment instances. When collecting and auditing the existing data they have in these areas, the team realises they have ample transaction data to hand, but currently lack insights into customer satisfaction and reasons for cart abandonment. To put it another way (and make us sound way smarter in the process), the team has quantitative data but lacks qualitative insight of any real value. As a result, the team acknowledges the need to collect new insights from a wider range of sources.

Step 3: Collecting new data

With data gaps now identified, the team must begin implementing the tools and approaches to gather the necessary feedback. They know it’s vital that this is done strategically, and so set clear objectives and a sufficient time frame for the amount of data they need to gather - feedback from two users simply isn’t representative of a site that gets thousands of visits per month! So, the team implements customer feedback surveys and integrates a tool to track cart abandonment reasons, and leave these running for long enough to collect a sufficient sample size that ensures their insights are both informed and valuable.

Step 4: Analysing the data

With both existing and newly gathered data, the team performs a comprehensive analysis. They identify key factors leading to cart abandonment, such as complicated checkout processes and unexpected shipping costs, and discover that customer feedback points to desired features and products not currently offered.

Step 5: Actioning the analysis

Based on this analysis, the retailer simplifies its checkout process, provides clearer information on shipping costs, and expands its product line to include highly requested items. They also introduce a customer loyalty programme to improve satisfaction and retention. The result? By uncovering the right data, from the right sources, at the right points, the team was able to make purposeful and well informed decisions that helped them achieve both their primary and secondary objectives.

As simple as that?

It’s crucial to understand that the journey with data doesn’t end with its collection and initial analysis. In fact, that’s only the beginning - the real magic happens when this data starts to inform and drive your decisions. That’s what ultimately accelerates you towards achieving your goal. 

But unfortunately, it’s never quite that easy. 

To fully harness the power of data, it’s key that you remain agile and adaptable. As a rule of thumb: the deeper you dive into your data, the more flexible you must prepare to be

That’s because the more data you collect, the more likely you are to uncover information you hadn’t anticipated. Perhaps you uncover a piece of data that directly contrasts a regular assumption you’ve made about your customers’ buying habits, for example. 

In these situations, it’s important to embrace the adage of ‘the numbers don’t lie’. In the face of new and unexpected insights, don’t just ignore the ones that don’t fit your narrative, but instead adjust accordingly. 

That includes instances where these impact your primary and secondary goals, too - being flexible means allowing these new insights to refine or even redefine your strategies. It’s not about abandoning your goals entirely, but rather ensuring they evolve as you uncover more about your customers and your market.

This is where the clarity of your objectives really comes into play. For instance, if your goal is to enhance customer satisfaction, every piece of data analysed—be it feedback scores, website analytics, support ticket themes, or user behaviour patterns—should guide you in making informed decisions. These decisions could range from product adjustments to service improvements, all aimed at hitting your predefined targets. 

Whatever decisions you make, the trick is to always ensure your decisions are guided by the data, rather than shoehorning data to fit with your decisions

Incorporating data into decision-making processes in this way is no longer a nice-to-have; it’s a necessity for staying competitive. And the good news is that there is an array of exciting tools to make sense of these vast data landscapes, from AI-powered analytics platforms to more straightforward data visualisation software. 

Just ensure these aren’t overly complex to the point of convoluting your analysis and misaligning your insights and objectives. Sure you want to uncover as many insights as possible, but you always want these to keep illuminating the path towards your North Star KPI and end goals. 

To do this most effectively, you must understand that the true power of data comes in the fact that it’s never a one-and-done affair. Working with data is a cycle of continuous improvement, and regularly revisiting goals, the data supporting them, and the outcomes of your decisions ensures that you’re always remaining on the right track. 

The continuous evolution of data and the real-time insight it provides is invaluable. Making incremental changes that steer you closer to your objectives, informed by the latest data, not only keeps your strategies fresh but also responsive to the ever-changing business landscape. 

To put it another way: data is a journey, not a destination.

Remember that the first step in your business’s data journey is to set clear, actionable goals. From there, the world of data opens up various roads of possibility to drive your businesses forward. Whether you’re just beginning to explore the potential of data or looking to refine your approach, the goal is not just to collect data, but to let it guide you towards your objectives in a meaningful way, and knowing how to utilise this approach is one the most effective weapons in any company’s arsenal.

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