Before we dive in, let’s align on a few terms. Analytics is a blanket term that describes the process of collecting and interpreting information. It is almost always used in the plural form, just like “women’s studies” or “shenanigans” — you would never talk about one analytic or another. For this, we use the term, metric. Metrics are specific measurements, usually quantitative, that we obtain in order to answer a specific question. Temperature is a metric we use to answer, “How hot is it?” Pressure is a metric that answers, “Are my tires inflated?” In short, every metric is a quickly interpretable piece of information.
You have probably heard the term KPI, or Key Performance Indicator, thrown around in a meeting or two. KPIs are simply a subset of metrics that provide insight into how well an organization is tracking against its critical objectives. You may be interested in your total employee count as a metric, as it’s helpful to understand your growth rate and answer some important legal questions, but it’s unlikely that having 100 employees by 2023 would be a business objective, so employee count, in most cases, is not a KPI. On the other hand, employee count can be used to calculate another metric: profit per employee (or sometimes revenue per employee), which signals the efficiency of a business and allows comparison of that efficiency across businesses within and between sectors. If increasing efficiency is important to you, profit per employee might be a KPI you’d want to track. In 2019, financial giant Fannie Mae reported the highest profit per employee of any company in America, coming in at a whopping $1.9 million per employee in profit. Not a bad goal to aim for, right?
Note: As an e-commerce company, beating Fannie Mae at profit per employee would actually not be a realistic goal. Financial companies from that same data set averaged $119k per employee in profit, while the closest retail industry sector (apparel) averaged $26k. It is always important to look at metrics in context, which we will discuss in more detail later.
For the rest of this series, we’ll be using the term metric instead of KPI, as it is more general, but remember that any metric can be a KPI. It just depends on what is important to your business at the time.
You probably have a good sense of this by now, but for the sake of completeness, let’s discuss why it’s so important to track metrics in the first place.
Say you wanted to know how satisfied your customers are. You could try a few qualitative approaches:
These may provide you with some good anecdotal evidence about the general themes, but can you really make an overarching decision with confidence? And how will you know if you’ve improved next month when a whole new batch of stories come in?
An easier way of doing this is utilizing metrics, quantitative indicators of customer satisfaction. In the case of reviews, this usually comes in the form of a rating, often on a 5-star scale. Customers themselves have great confidence in this method, so much that an estimated 70% of new customers identify businesses by using rating filters — the most common filter showing only businesses with a rating of 4 stars or higher. They do this because the average rating provides an immediate understanding of a business quality, saving them time and giving them confidence in their search.
Internally, the average review rating can be tracked over time to show clear changes in customer satisfaction. Metrics other than the average may be important as well, such as the percentage of 1 or 2 star reviews (the goal obviously being to minimize these). While review ratings are helpful for customers to see, a more common internal measurement of customer satisfaction in e-commerce is the Net Promoter Score (NPS), which we will cover in a later section. Both of these are examples of using metrics to answer important business questions, and both are easier to interpret and to set goals against than receiving verbal updates from the sales team or reading individual reviews.
Note: Quantitative metrics can be generated from qualitative information such as review content using techniques such as text classification and sentiment analysis, but these are a little more challenging to implement.
There is no one-size-fits-all answer to this question, but there are some steps that can help you arrive at your own. The first goal is to articulate where you are trying to go as a business. It’s likely you’ve already done this at the time of founding, or maybe kicking off the year, but it’s worth checking in before you go targeting metrics to make sure you’ve still got a relevant destination in mind. Then you have you figure out where you are, specifically. “Who is buying our products? How much are we selling? Are we turning a profit? How is our brand perceived?” These are just some of the many questions you may ask, and the answers to these types of questions will help you define where you are. (Note: If you stumble upon a question with no clear answer, that’s a pretty good sign that there is a related metric you could start tracking in order to get one.) Once you know where you are and where you are going, then you can start charting your course — laying out a strategic roadmap for how you will get from A to B. Some specific exercises that can help with this sort of diagnosis and planning are SWOT, PESTLE, and 5 Forces analyses.
The plans in your roadmap will nearly always have a related set of metrics that will help you measure your progress along that journey. If you want to increase sales (you usually do), you may consider tracking qualified leads generated, conversion rates, or average order volume. If revenue stream diversification is important, perhaps sales by product category or market segment is worth tracking. For customer satisfaction, net promoter score, customer retention rate, and return/exchange rates might be most useful.
It may be tempting to try and track everything you possibly can, but remember that ultimately you will need to review, interpret, and make decisions on these metrics, and are you really going to be motivated to read a report of 172 metrics every month to see how your business is doing? Just like when setting your strategic goals, you should focus your attention when creating an analytics plan.
Some metrics are deceiving. They may look impressive on a slide in a board meeting, but they don’t really give you any useful information. These are referred to as vanity metrics. They’re worth mentioning because it is very tempting to include these, and they’re not always easy to spot. Common examples are total social media followers, ad impressions, page views, total all-time sales, and all-time customer count. There are many others that could apply to your specific situation, and even if you see other businesses tracking something, it may be much more important for them than it is for you.
Similarly, not all metrics traditionally considered vanity metrics are necessarily worthless to your business. Say you’re trying to generate buzz about an upcoming brand, and you know that a customer needs to interact with your brand multiple times before a sale is made. You might try to get a head start by running ads that simply expose them to the new material without the expectation of a conversion. In this case, impressions might actually matter to you and might be something you actively work to increase.
A great litmus test for judging the value of any metric is asking two simple questions:
The best metrics are those for which the answer to both these questions is a resounding “Yes!”
Once you’ve decided on your key metrics, it’s best practice to set some targets to aim for. The popular SMART goals technique applies here too. Metrics by their very nature are already specific and measurable, and if you’ve chosen them using the methods we’ve laid out above, they will certainly be relevant to your business. When it comes to your target values, you’ll want to check these for relevance as well. You may indeed want to track cart abandonment rate, but if you’re sitting at 40%, far below the e-commerce industry average of 73%, does it really make sense for you to spend time and effort to push this down farther, or are there other battles that can be won while you just keep an eye on this metric for now?
The “achievable” part of the SMART acronym is also important here. No one likes being held accountable to goals they can’t realistically achieve. Setting goals that are reasonably within reach is important for the mental health of you and your team. Sure, it’s ok to have a long term vision, even encouraged, but set your near-term targets so that you can get some small wins under your belt as you get your analytics efforts underway.
Context will be critical when both planning and reviewing your metrics. First, you should consider a metric in the context of other metrics. It might feel great to see a strong increase in product sales, but if your return rate is high, or if your team had to discount the product heavily to get it out the door, are those sales actually as valuable as they appear? This is why viewing metrics together is often important. One way to do this is dashboards, another is by using calculated or aggregated metrics, which combine multiple metrics into one value that provides you with more information. We’ll discuss both of these topics in more detail later in the series.
Even when you can see the other metrics that support your metric of interest, they should not be considered for a single point in time. Keep in mind the “where you’re going” and “where you’ve been” positions identified earlier, and consider these when reviewing the metric. How far are you from your target? Even if you are still far, have you made an improvement over last month? How many months in a row have you made improvements? These are all relevant questions that will help you understand not just your current state, but also your trajectory. It is almost always a good idea to present your metrics along with time series data that show their trend over the past 3-6 months, rather than just providing a snapshot every month. It’s also a good idea to show the target on whatever visualization you provide, so it’s clear how far you have to go.
Our last point on context was mentioned once already but is worth revisiting here — industry benchmarks. There are metrics that are commonly tracked across all businesses. We shared that the average profit per employee in apparel was $26,000 and that the average cart abandonment rate in online retail was 73%. You may also be interested to know that the average e-commerce conversion rate is a little over 2%, or that the average customer lifetime value is $168. These values can provide you some insight into what reasonable targets might be, but these should be viewed with extreme caution. If you’re in your early years of growing a business, what other established businesses are doing is not particularly relevant to you. Also, are your products the same? Are you operating in the same regions? Probably not. There are a lot of factors that make business-to-business comparisons difficult, so it’s really much more important to focus on yourself. Have you improved your metrics? Are you moving towards the targets that are important to you? Is your business turning a profit while bringing joy to your customers, your employees, and to you? It’s good to have these external numbers in the back of your mind, but don’t put too much pressure on yourself to match them.
By now we hope you’ve got a good understanding of why metrics are important for your business, how to align them to your goals, and how to interpret them once you start taking measurements. In the next part of this series, we’ll review the metrics we find most useful in e-commerce, and finally in part 3, we’ll walk you through some detailed collection and analysis methods for operating at scale. If you’re ready to get started on your analytics journey, we are always here to help!