Data-Informed vs Data-Driven: What’s The Difference?

Businesses rely on data to formulate growth strategies. A data-informed and a data-driven business are two unique approaches to leveraging data to make your brand stand out.

Updated: July 27, 2021
Data-Informed vs Data-Driven: What's The Difference?

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As data pioneers, we always encourage businesses to leverage whatever stats are available to them when making decisions. 

However, the way you do this matters a lot, and that has given rise to several terms.

  • Data-informed vs data-driven: what should you be? 
  • Does data make your business decisions, or do you make your decisions using data to help? 
  • In simpler terms, does data drive or guide your business decisions?

Though the difference between these buzzwords is subtle, each approach is significantly different and changes your company’s relationship with data.

Taking a data-driven approach where data drives everything you do might be the more objective approach, but you may miss the bigger picture as a result.

On the other hand, going all-in on the data-informed approach and allowing data to guide your business decisions gives room for too much flexibility in your data. 

Just think about what might happen if you start cherry-picking data based on preconceived notions.

So, are we saying that both approaches are inadequate, and should you just do away with them? 

Not quite. Stick around to find out why.

    What is a Data-Driven Approach?

    If we took a data-driven marketing approach, it would imply that we rely on data to make our decisions all the time. 

    In other words, every aspect of our business strategy depends on our interpretation of available data. 

    This approach is excellent where we can harness data for unique insights and information on your customers.

    But, as you can already tell, the data-driven approach does not take personal experience into account. 

    ➤ It focuses less on the bigger picture. Simply put, it is all about the facts, where data has the final say.

    Here’s a typical example: we have two copies of an ad, A and B. 

    From our view, ad A seems better, and we think that it might yield better results. However, instead of running ad A, we go on to A/B test both copies. 

    On evaluating their performance, ad B turns up with a better (lower) Customer Acquisition Cost (CAC).

    We were pretty sure that ad A was the better one, though. It is such a shame that we will have to use ad B because we are strictly data-driven.

    See what we mean?

    Pros of a data-driven approach

    Here’s how we think of it. 

    Since being data-driven basically takes decision-making out of our hands, it prevents personal bias. 

    Simply put, it tells us what to do, and we do it without gut instincts coming into play. 

    Plus, we would not need to go through the nuances of decision-making — and some businesses love that.

    As a follow-up from the first point, decision-making being out of our hands makes it easier for us to push back against stakeholders who may have their own agendas. 

    Who doesn’t like defending their position with cold hard facts and figures?

    Another advantage of a data-driven approach is that it can help us identify trends that may signal future problems. 

    Rather than reacting to market changes, we can identify potentially problematic situations using data.

    Cons of a data-driven approach

    Placing sole emphasis on data to make decisions may cause us to miss the bigger picture.

    Another major problem with the data-driven approach is that we may be relying on data that is not statistically significant. 

    This will undoubtedly prevent us from making informed decisions. 

    In fact, if we are truly to go the data-driven route, we must collect large data sets over a relevant period to get an accurate representation of market conditions.

    A purely data-driven approach is challenging. 

    While 74% of businesses aim to be data-driven, only about 29% are good at transforming their data analytics into action.

    What is a Data-Informed Approach?

    Taking a data-informed approach means using data alongside other inputs like:

    • User research.
    • Personal insights.
    • Experience to make decisions. 

    ➤ This means that data makes up just one part of your decision-making process.

    Let’s go back to the previous example.

    We’ve set up an A/B test for both our ads: A and B. However, both ads haven’t been running long enough to meet our sales cycle, so we can’t evaluate their performance with CAC.

    We decide to use the Click-through Rate (CTR) to evaluate performance. 

    On checking, ad A returns a higher CTR than ad B. If we followed a data-driven approach, we’d turn off ad B and leave ad A running since it has a higher CTR. 

    However, since we are now using a data-informed approach, we’ll focus on the bigger picture.

    From our findings, ad A does have a higher CTR, but it also has a higher cost per click (CPC). 

    This means we’d burn through our budget way faster if we continued to run it. 

    Also, bringing our past experience into the mix, we know that both ads have higher CTRs than our average performance for the metric. 

    This means that we will still get a better performance, regardless of which ad we promote.

    So, which do we ax? 

    Since we are now data-informed, we will turn off ad A because we want our budget to be as effective as possible without compromising performance. 

    But remember that ad B still returns better values than we previously had.

    Pros of a data-informed approach

    A significant benefit of the data-informed approach is that it allows us to see the big picture.

    It gives us quality, not just quantity. 

    That means we can combine other inputs with our data to understand better what is going on, discover unique solutions and make decisions based on the complete view.

    Rather than being all straight-faced and data-focused, a data-informed approach allows us to solve business problems with relatively unorthodox solutions. 

    In other words, we blend data with other factors like our business experience and an outside-the-box approach to problem-solving to come up with solutions that pure data may not give us.

    Additionally, a data-informed approach allows us to keep up with early changes in trends

    For example, if our users were adjusting their preferences due to a competitor or industry change, we’d be able to catch it early on.

    If we were data-driven, it would probably be too late by the time we notice the change. 

    Of course that a data-driven approach helps us catch potentially problematic situations. 

    So here is how we like to think of it.

    Data can tell us if sales or user subscriptions are taking a dive, but we need to be data-informed to know that changes in consumer preferences or competitor offerings are the factors causing the change.

    Cons of a data-informed approach

    Our biggest issue with the data-informed approach is how easily you can be swayed by outsiders. 

    Take the previous scenario of opinionated stakeholders, and you might have more difficulty convincing them since you are using other inputs besides just data to make decisions.

    How easy would it be to choose what data to accept and which one to reject based on our desired outcome? 

    We find that it is relatively easier for personal biases to come into play, perhaps, even unknowingly, in a data-informed approach.

    We have all had that moment when there were so many options we could not make a choice. 

    This could also happen in a data-informed strategy. It can lead to choice paralysis due to too many inputs. 

    Data-Informed vs Data-Driven: Which One Is the Best?

    Both approaches have their pluses and minuses, but does one truly excel the other?

    We find that the data-driven method is best for companies with a big data approach.

    It is our preferred method for “either/or decisions”. 

    Being data-driven will work for you when you are focused on optimizing your conversion rate, improving pricing or performing A/B testing.

    Let’s take the example of A/B testing. 

    When A/B testing a single metric, your answer can only be A or B. This kind of decision can be data-driven, and personal experiences rarely come into play. 

    Your primary focus should be on choosing your success-defining parameters beforehand. Plus, where relevant, you also want to gather enough data to get significant results.

    On the other hand, we find that the data-informed approach works best for complex projects that combine various inputs. 

    For example, if we were going to update our eCommerce store, we would have to focus on more than just data. 

    Inputs like customer feedback, personal experience, competitive data, and stakeholder input, amongst others, will come into play.

    A data-informed approach will also be best for processes that rely heavily on creativity. Here, a combination of data and personal experience will also come into play.

    So, Which Approach Should Your Business Pick?

    In this drawn-out data-informed vs data-driven battle, you could go full-on data mode and make those stakeholders eat their words, or you could take the informed route by combining multiple inputs.

    But, what if we said you could do both?

    ➤ We think that finding a balance between the data-driven and data-informed methods is the ideal way to go to give your company a competitive advantage.

    However, as we have already mentioned, the method you will use will depend on the circumstances.

    Generally, whenever you need to make decisions based on quantitative input, you can use a data-driven approach. 

    If the decision requires some elements of qualitative input, you can follow the data-informed route. 

    Whichever you choose to do is up to you. In the end, you have to understand that there is no clear winner between both approaches; it all depends on the particular setting.

    Bonus Topic: Meet the Data-Inspired Approach

    Here is an additional method: the data-inspired approach. 

    This method involves using intuition, creativity, and past experience to spot trends in a variety of data. 

    It entails bringing different sources together in an attempt to find common ground between them. 

    When it comes to generating new ideas and developing innovative strategies, there’s might be a place for the data-inspired approach in your business decision-making process.

    But be advised: “inspired data” must never be seen as concrete data. 

    It is risky to draw serious conclusions from this data — although, depending on the situation, you should bet on it, since it could shed light on previously obscure areas.

    Wrap Up: Leverage all Data Mindsets based on Specific Circumstances and Expectations

    It will improve the amount and relevance of the insights you get to work with.

    In the end, it’s not really about the “data-informed vs data-driven” dispute. 

    It is all about recognizing those yes/no situations, those complex scenarios that require multiple inputs, and those moments of pure inspiration to determine which route to take.

    Eventually, whether you go the data-driven, data-informed, data-inspired route or combine all three, there’s no denying that data has a role to play in your decision-making process, and rightly so.

    That’s why you need to take conscious and deliberate action to make the most of your data collection and utilization process.

    Start by learning everything about data monitoring and how it helps you make strategic decisions!


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