One of the benefits of marketing in the 21st century is the availability of data.
As marketers we’re obsessed with tracking every little detail about each of our customers: Where did they come from, what did they do, what did they not do… and many other questions all come into play.
The problem with data
The problem is the sheer volume of data available! This inevitably results in some companies not knowing where to start, and therefore they choose to look at every metric instead of narrowing their focus on the ones that matter.
As a result of this, many organisations fail to see the benefits of their data because they don’t understand exactly where each individual metric fits into the overall jigsaw that is data marketing.
Most of the time this comes from looking at metrics as a single indicator without cross-reference, and using them as what we call ‘vanity metrics’.
For instance, looking at overall sessions and concluding that traffic is down and therefore it must be an SEO problem is somewhat problematic. There isn’t enough granularity in the data to decipher that organic traffic is the problem, and, in fact, search traffic may be up 10% year-on-year but it is blinded by incorrect use of the data.
Likewise, it is similarly risky to take a break when you notice that traffic is up when actually your e-commerce business is making no sales and ultimately no revenue. Vanity metrics are dangerous to focus on without something to counter and reference against.
Reporting on everything
Another common problem is reporting on too much data (or ‘data puking’, as it’s known in the web analytics world). On his blog, Avanish Kaushik provides a brilliant post on Web Reporting vs Web Analysis describing this problem.
It’s not possible to report on every metric, and nor will it give better insights. All it does is transfer the data from one medium to another, and in moving the data from your Analytics package to Excel you still have raw data, not actionable insights.
Both of the above problems arise from the same mentality: report creation without a clear goal. With no clear goals you can only get the raw data, because what is there to measure success against? As such, reports end up bringing as much data to the table as possible without a thinking where each metric fits.
Fewer metrics, more insights
Reporting on fewer metrics allows you to focus your efforts, and will also make you think about what the metrics mean and how they connect together to reach your business goals.
By working backwards from your goals to your report, you can choose metrics that are important to each KPI and work in synchronicity to bring actionable insights.
Start by taking a step back away from your Analytics package. The goal here is to think about why your website exists: Are you looking to generate leads? Sell products? Relieve traffic from your customer service phone number? Once you know this, you can begin to work backwards from the end goal creating a selection of KPIs that are important to fill out the data jigsaw.
Each KPI you set should have a couple of performance indicators attached to it, and this is where your metrics come into play. Choose metrics wisely, and pick ones that will give you an indication of performance but that also feed into the overall goal.
Reporting is reactive; analysis is proactive
It’s not about reporting on every metric within your Analytics package. It’s about reporting on the right metrics for your goals to give you an indication of overall performance. That way if something happens within your set of metrics (good or bad), you know you need to investigate what has occurred and why.
Taking the emphasis away from reporting and placing it on the analysis which is where actionable insights can be found.
Example KPI setting
For example, the top line of a lead generation website is simply how many leads are we generating. From a reporting perspective, we can just provide the goal completion number to our manager, which is OK but doesn’t provide any opportunity for improvement… and doesn’t even tell the whole story.
Businesses want to improve and increase the number of leads to better their bottom line. Instead we should break this down: while the sales team may want to know how many leads have come to them, they may also be interested in the amount of leads they successfully close. Useful metrics could be:
- Leads delivered from marketing
- Leads converted
Likewise, while the marketing team may care about the number of leads they have created, they may be more interested to show which channels drove these leads. This will demonstrate how they can optimise their marketing efforts for better ROI in their budget.
For example, SEOs may want to know:
- Organic search traffic to the website.
- Click through rate
- Conversion rate
Campaign Managers may need to see:
- Landing page traffic
- Landing page conversions
Email marketers may aim to improve:
- Open rates
- Click through rates
- Traffic to the website
All of the above examples focus on delivering insights into the overall goal of understanding how our website is performing and how the leads generated create our business revenue.
Each member of the team needs to look at different metrics to understand their contribution. Smaller numbers of metrics give more time to focus on optimising and improving through data analysis, rather than increasing how much resource is spent data reporting.