Online retailers juggle thousands of ecommerce metrics, week in week out. Customer journeys, hundreds of products, multiple revenue streams and more add up to huge amounts of (valuable) data. And each year, the amount of data we collect grows. It’s commonly reported that 90% of the world’s data was collected in the last two years alone. If this eye-popping stat is true, then it’s impossible to imagine how much data online retailers are set to gather over the next decade.
But it’s also becoming impossible to keep track of. Traditional approaches to KPI tracking are struggling to cope with the sheer mass of data that needs to be analysed in order for businesses to remain competitive. And this is why automated KPI tracking is so extraordinarily beneficial for online retailers today.
What is automated KPI tracking?
Automated KPI tracking is a method KPI analysis that uses machine learning to scan through your datasets, dashboards and ecommerce metrics 24/7. It learns the normal behaviour of your data, and picks up anomalies and overlooked digital performance opportunities in ecommerce KPIs immediately. The AI then alerts you to any unusual behaviour in their data in real time, allowing them to drill down into the cause before it impacts revenue and conversions. (You can read more about how AI automates KPI tracking in this handy guide.)
Here’s some of the key use cases for automated KPI monitoring in ecommerce.
1. Avoiding pricing glitches
Back in 2010, Zappos infamously lost $1.6 million as a result of a pricing glitch. This is the kind of error that keeps online retailers awake at night. Unfortunately, anomalies like this are easily overlooked, and a pricing glitch on one product can result in thousands, even millions, lost.
Setting alerts to notify teams of when this occurs is one solution to this problem. But the issue is that, when dealing with thousands upon thousands of products, setting alerts for each individual product SKU becomes virtually impossible. Plus, traditional KPI monitoring tools can only catch pricing glitches like this after they’ve already affected revenue. So, when they are detected this way, companies are forced into a lose-lose situation: Either they have to honour the lower price and damage their (already-tight) profit margins – or risk losing valuable customers.
Luckily, autonomous KPI tracking picks up price glitches like this instantly. Anomalies, such as unexpected spikes in product demand, that indicate a pricing glitch are detected as soon as they occur. This means your team is alerted straight away to the issue and can fix it before keen-eyed customers flock to the under-priced product. With AI keeping a eye on your ecommerce metrics, margin catastrophes are detected in real time, before your entire margin gets wiped out.
2. Detecting spikes in cart loading times
1 out of 5 online shoppers will abandon their cart because the transaction process was too slow, so spikes in cart loading times can be utterly devastating for any online retailer. But picking up on these anomalies isn’t easy. Spikes in loading times on specific pages are tricky to detect if the average page load time is still better than the site average when looking at an aggregated timeframe.
However, with machine learning automatically tracking your online store’s KPIs, anomalies on any one of your page loading times will be detected as soon as the problem arises. This means you can deal with issues on each individual page before they affect user experience or your bottom line.
3. Identifying poorly-optimised keywords
Online retailers today use hundreds of campaigns and thousands of keywords to target the greatest number of customers. But this makes it incredibly difficult for them to analyse and optimise campaigns on a daily basis. This means that poorly-optimised keywords often end up being used, and precious time and money is wasted before they are discovered.
But, with autonomous KPI monitoring analysing your campaigns 24/7, the poorly-optimised keywords causing under-performing ads are spotted immediately. Armed with this information, you can easily and directly optimise keywords and supercharge your campaigns, guaranteeing more revenue per marketing dollar spent.
4. Alerting you to overspending on ads budget
Daily campaign costs can end up running up to 2x the set daily budget, depending on traffic fluctuations and algorithms. As a result, ad budgets need to be constantly monitored to ensure that the cost of campaigns is fully optimised and provides the best ROI. This is especially true in ecommerce when profit margins are already so tight. Yet, with hundreds or thousands of campaigns on the go, monitoring spending to ensure that overspending isn’t happening is incredibly resource-intensive. Either the online retailer’s marketing team are going to have to spend all their time combing through the data, or opportunities to optimise the ads budget will be missed. This could add up to hundreds of thousands over the course of a year.
However, with autonomous KPI monitoring, overspending becomes incredibly easy to avoid. With AI analysing your marketing dashboards 24/7, you’re alerted to daily cost spikes so you know exactly when overspending is occurring, without wasting time, resources and manpower sifting through hundreds and thousands of metrics. You’ll benefit from better-optimised campaigns and tighter margin control for your business.
5. Uncovering hidden revenue opportunities
Profit margins in ecommerce are notoriously tight. As a result, online retailers are always on the lookout for ways to improve their revenue and stay ahead of the competition. But revenue opportunities don’t necessarily show up in the metrics that ecommerce teams have decided are the most important and are regularly checking. Without a granular view on all their KPIs across all dashboards, online retailers often miss valuable revenue opportunities.
With autonomous KPI monitoring, all your ecommerce metrics are monitored with machine learning, meaning that any and all performance opportunities in your data are revealed when they occur. This direct view into your individual metric fluctuations allows you to quickly take action to drive revenue further.
6. Saving money lost between Clicks and Sessions
The average ad conversion rate hovers at about 3.75%. That means that for every customer that clicks on an ad and converts, dozens are lost along the way. So, online retailers finding a way to make that percentage as high as possible is critical to ensuring more revenue per marketing dollar spent. This means the ads that are losing traffic between clicks and sessions need to be fixed as soon as possible.
But, when a company is running hundreds of campaigns at once, identifying the poorly-converting ones can be difficult. And even when those campaigns are found, understanding why users are clicking but not converting isn’t easy because it could be for any number of reasons, from misleading ad messaging to broken or poorly-constructed landing pages. Often, poorly-optimised campaign are left running for weeks on end.
However, with automated KPI tracking, the campaigns that aren’t converting will be flagged immediately. The machine learning algorithm will identify the metrics at the root of the issue for your team to further investigate. This means that you’ll be able to see immediately its a technical issue, like a broken link, or a deeper problem with the marketing messaging.
7. Identifying tracking errors
Tracking errors can be an invisible problem threatening the success of an ecommerce business. With online retailers tracking so many ecommerce metrics, it’s hard for them to account for misplaced tracking code at an individual level. This means that they can end up relying on data that’s flawed, and make decisions that damage the business as a result.
This issue is easily solved by automated KPI monitoring. Metrics that are behaving unusually are identified immediately so you can investigate why this is, and identify the KPIs that have been given the wrong tracking code. With you online performance fully monitored by an AI, you can make the best decisions for your online store.
8. Picking up on new browser updates
Browser updates are another thing that can unexpectedly trip up online retailers. Browsers are regularly updated, and, when they are, this can impact the performance of web pages and apps. Ecommerce teams must closely monitor these updates to make sure their site is optimised for the most recent version. If they miss new versions, this can lead to days, or even weeks, of downtime for certain users. But with traditional KPI monitoring, issues with new browsers can continue until the team notices an impact on revenue or conversion rate and has to look deeper into why.
This problem is quickly solved when you’re using automated KPI monitoring, however. The machine learning algorithm swiftly picks up issues with pages not working, before they have the chance to impact revenue and alerts the relevant users. With this information, the tech team can make a quick fix, reducing downtime and protecting conversion rates.
9. Automatic monitoring of ad agencies performance
Given the scale of advertising many online retailers implement, its common for them to use ad agencies to stay on top of their campaigns. However, agencies do not have the same incentive as the retailer to make the most out of the budget. In fact, agencies are often incentivised to spend as much of the money as possible, even if it doesn’t result in more conversions, because this results in higher profit margins for them. Often, there’s little transparency in how budget is being spent by agencies. But, most companies don’t have the time and resources to monitor the individual metrics across hundreds of campaigns to make sure the agency isn’t short changing them.
With automated KPI tracking, this kind of granular monitoring becomes much easier. The AI can alert you to any unusual activity in the campaigns, rather than you having to get an employee to comb through the data of hundreds of campaigns. This lets you clearly see if the decisions made by the ad agency are in your best interest – or there’s. Armed with this sort of information you can closely monitor the agency you’re working with and push them to perform better if necessary. That way, you’re empowered to get the most value from a key business relationship.
10. Finding valuable insights without the need for an analytics team
It’s a-given that the amount of data coming in and out of an online store is too much for any human to comb through. But if online retailers can’t see all of the data, they could be missing out on valuable insights. Realistically, to understand all the data, identify issues and uncover key digital performance opportunities, businesses need to recruit in a whole team of analysts. This is a costly investment, and one that’s difficult to ensure since data talent is in short supply.
Luckily, automated KPI analysis provides the horsepower of an army of analysts. And since machine learning is so effective and reliable, it discovers things that human eyes can’t see. This means you can ensure much closer monitoring for a fraction of the price – and your analysts can work on data projects and innovation that will help you stay ahead of the competition instead of spending all their time on KPI analysis.
Key benefits of automated KPI tracking
So, what are some of the key benefits of using automated KPI tracking? Well, with machine learning tracking your ecommerce KPIs, you can enjoy:
- More granular insights into your ecommerce KPIs
- Much more reliable KPI tracking, with an AI that picks up details in your dashboards that humans can’t see
- Instant alerts of unusual behaviour in your ecommerce metrics, empowering you to identify overlooked anomalies and digital performance opportunities that increase conversions and revenue
- The power of a data analytics team, without the cost or talent drain
- Stronger, more empowered business relationships
- Optimised ecommerce campaigns
- Immediate detection of any technical issues on your webpages, reducing downtime and increasing the rate of conversions
How to get started with automated KPI tracking
Get started with automated KPI tracking by signing up to the Millimetric platform for free to see the performance gains you can achieve with automated KPI tracking. Or contact us at email@example.com for more info on our bespoke Enterprise model that comes with full customisation to suit any workflow, agency-style consulting from our team of specialists and fully-supported set up.