Effective data analysis and KPI tracking is a challenge for every business. And it’s a challenge that’s getting more difficult by the day. The amount of data we track to gain valuable business insights is on the increase. Today alone, we will generate about 2.5 quintillion bytes of data. By 2025, that figure is projected to reach 463 exabytes (an unimaginable number, but, for reference, that’s the equivalent of 212,765,957 DVDs).
Yet, despite the amount of data available and the pressure to become more data-driven, between 2017-2019 the number of organisations describing themselves as ‘data-driven’ dropped from 37.2% to just 31%.
The sheer amount of data we have available to us today should be a great thing. It should be leading to supercharged customer journeys, the digital transformation of whole industries, unbelievable innovation and more. But, for many, it’s not. In 2011, McKinsey predicted that data and analytics was going to revolutionise work, pointing to five industries in particular: The public sector (EU), health care (US), manufacturing, retail (US) and location-based data. Yet, as of today, just a fraction of their expectations have been reached.
We simply aren’t where we expected to be a decade ago. So what’s holding us back?
Why are we still struggling with data analysis and KPI tracking?
There might be a huge amount of data to analyse now, but, given the strides we’ve made over the last decade, why is it still overwhelming us? Why are 65% of organisations saying they have ‘too much’ data to analyse?
Today, there’s three key things that are holding us humans back from being able to fully analyse data and KPIs at scale:
- Time constrictions. We only have so many hours in the day. Most employees simply don’t have the time to conduct a truly thorough analysis of data, and so valuable data insights fall through the cracks.
- Money. Investing in teams of data scientists or the costly BI tools needed to conduct data analysis at scale is an expensive investment that many businesses simply cannot afford.
- Limited talent. On top of all this, hiring data talent is increasingly difficult.
Unless you’re able to overcome these challenges (and most businesses who aren’t in the Fortune 500 simply don’t have the resources to do so), making full use of your data and thoroughly analysing and tracking your KPIs is nearly impossible. This is why a whopping 60-73% of data goes unused in analytics. Just think of how many valuable insights are being lost every day.
The solution? Artificial intelligence (AI), and its ability to automate data analysis and KPI tracking.
How does artificial intelligence automate data analysis and KPI tracking?
We aren’t going to delve too deeply into what artificial intelligence (AI), or, more specifically, machine learning, is and how it works (you can read about that here instead). But, for the purposes of this article, you just need to be aware that the technology is incredibly effective at crunching data and recognising patterns – two things humans tend to be terrible at.
Because it can do this so well, machine learning algorithms are able to scan through multiple datasets, over and over again, to identify any unusual patterns or behaviour in the numbers, 24/7. It can then alert the user to anomalies in their data as well as unearthing digital performance opportunities. Because this data analysis is being done by a machine, it can be done faster, more efficiently and at a much greater scale than even the most experienced team of data analysts can.
This means that when you put an AI to work analysing your datasets and your KPI dashboards, it will constantly monitor all your data, alerting you to strange behaviour without the need to invest excess time, money and talent. With a much more thorough analysis of all your data, you can be much more competitive, even with industry Titans who have hundreds of the best data scientists at their disposal.
Let’s have a look at the three key benefits of having an AI automate the process of data analysis and KPI tracking.
Key benefit #1: Deeper analysis of your KPIs
Humans simply aren’t meant to analyse data, day in day out. Scanning through dashboards is mindless work, and so we inevitably miss out on things. As a result, many companies focus on a few KPIs that they decide are the most important. While this approach is more scalable, it still means missing out on potential anomalies and digital performance opportunities that appear in the KPIs you aren’t looking at.
For example, we worked with a client who noticed they suddenly had an unusually high cart abandonment rate. When they looked at the digital KPIs they tracked, everything seemed to be normal and page loading times were as expected. It wasn’t until they used AI algorithms to automate their KPI analysis that they noticed that their checkout page had a 10-second loading time, causing users to click off. This was an issue that only impacted one page, so it didn’t show up in their analysis. Yet by catching this problem, they prevented the loss of up to €120k a month in abandoned carts.
By relying on manual data analysis and KPI tracking, you could be missing out on opportunities like this to optimise your digital presence and maximise revenue.
Key benefit #2: Saves time, money and resources
Even if we were built to scan through datasets all the time, we’d still struggle to find the time to do so. Employees of data-driven organisations are already putting in a significant amount of time every week to analyse their data and KPIs. Marketers spend an average of 3.55 hours a week (280 hours a year) on data analysis, for instance. With so many other tasks required to keep the business running, it’s understandable that we can’t commit yet more hours to data analysis each week, even if it means missing out on deeper insights.
Even if you employ a data analytics team to do the analysis for your, the problem isn’t gone. It’s simply now the data analytics team’s job to crunch that data. This means they are spending huge amounts of time tracking KPIs when they could be working on innovative, data-driven projects that place your organisation ahead of the competition.
Fortunately, AI automated data analysis and KPI monitoring saves time, money and resources while still producing more effective and consistent results than a human can. This means you can cut out the time spent analysing data and building reports, because all the important information is delivered straight to you.
Key benefit #3: Real-time data insights
Finally, a real issue with analysing data and KPIs manually is that problems are normally detected after they’ve already had an impact on performance. This means that the issues have the chance to effect user experience and your bottom line before you even see them. You’re also forced to deal with all problems reactively, which normally adds to the time it takes to fix them. For example, if you’ve had a price glitch on a product that took you a few days to uncover, you’ll have to not only fix the error on the site, but deal with the customer service issues that arise with this too.
However, with AI data analysis and KPI tracking, small fluctuations in KPIs that could take days, weeks, or even months to appear with manual analysis are detected immediately. This is because the algorithms are so familiar with your normal data patterns and work 24/7 to identify anything that doesn’t fit. With AI data analysis, the user is able to swiftly deal with the problem before it affects performance. This ‘analytics on demand’ model means that your data can work for you, rather than you losing valuable hours of downtime on digital performance, campaigns and more.
How to use AI to supercharge your data analysis KPI tracking
Creating an AI algorithm that can scan your datasets and KPI dashboards 24/7 is a task for your data science team, if you have one. However, for teams without the time and resources, there are a number of BI tools on the market that can conduct automated data analysis and KPI tracking for you.
Millimetric is the most cost effective AI data analysis and KPI tool on the market today. It has a Free plan, a Growth plan starting at $99/month, and an Enterprise plan which builds a bespoke AI model for your company’s needs. Learn more about Millimetric’s pricing plan or sign up for a free trial today.