How Not to Drown in the Sea of ​​Marketing Metrics?

Content:

1. More data, more problems
2. 1. Don’t doddle around on data that doesn’t affect revenue
3. 2. Don’t confuse correlation with coincidences
4. 3. Investigate the relationships that really matter
5. 4. Share information to avoid unnecessary work
6. 5. Do Analytics, Not Visualization
7. What data can be analyzed in Dashly?

Getting information has never been so easy – all one needs to do is reach out. Marketers enjoy this more than others – there’s almost unlimited access to materials for their work. However, having all sorts of marketing metrics in front of their eyes, literally, smother them in the bottomless sea of data.

Flashing in front of the eyes, graphics of all shapes and sizes dazzle marketers and hide from them all the really important information. What’s the guarantee of the company’s growth? Why do customers buy what it is they buy? How can we make them buy more?

Marketers are responsible for the company’s profits but also for the losses. Therefore, even the most impressive marketing indicators will not mean anything if the revenue actually doesn’t grow.

More data, more problems

The constantly increasing volume of data (and the inferred opportunities for its analysis) only aggravates the situation. For two years the number of marketing automation software has increased by several times.
Not surprisingly, many marketers feel exhausted due to the amount of information and tools for processing.

The problem is that about 80% of this data doesn’t have any impact on revenues. Most of the tools and graphs on which your marketing department works so hard weren’t created to explain changes in revenue, or to even show new opportunities for obtaining it. You run a solid risk of getting into a vicious circle, where more and more data, less and less really useful information and ever-increasing fatigue.
How to cope with an abundance of data and focus on what matters?

1. Don’t doddle around on data that doesn’t affect revenue

Analyze and visualize only those metrics that are associated with revenue or the most important KPIs:

• number of visitors attracted to the site;
• cost of attracting 1 visitor;
• conversion (in registration, in payment, in re-payment);
• average check (or better – check by segments).

Learn more about key metrics and how to correctly calculate them you can in our prompt for SaaS and eCommerce.

If other data doesn’t make it clear, then it only distracts you from the analysis, which should tell the story of your success and influence the results.

Ask your colleagues and get the answer to the question “Which indicator will most accurately measure our success?” Identify such a KPI, and then it should become the basis for your data.

2. Don’t confuse correlation with coincidences

If the selected KPI is revenue, and you want to see how it’s related to, let’s say, activity in social networks, you can not simply start layering financial schedules on graphics of likes and retweets.

In November and December, for example, there’s always a peak of references to Santa and an increase to the company’s revenue. If these companies imposed social activity indicators on the sales schedule, they would thereby reveal the apparent dependence between Santa and sales.

Dependencies are useless, until you’ve carefully checked them and cleared them of noise. It may seem that short-term correlations are the cause of some events, but they can also just be a random accumulation of unrelated variables.

3. Investigate the relationships that really matter

Do not look for common coincidences: “Oh, look! These two indicators grow and fall almost synchronously!” Instead, look for patterns that predict key KPIs.

It may be interesting to know, for example, that your latest marketing campaign has brought a lot of money and made a lot of noise on Twitter. Ask yourself more specific questions such as: did you understand what steps can be repeated, what kind of optimization can be carried out?

Try to understand what caused each effect. The enthusiasm among certain groups of the target audience, the interest in the product or the rush among the fans of the star that you attracted to the advertising.

4. Share information to avoid unnecessary work

Growth is the business of every member of the team.
Marketers, analysts, SMMs and other professionals should work together. Openly share information and organize a workflow around which the team is mainly concerned about.

Every Monday, we in the Dashly, gather at the beginning of the working day for 10 minutes to discuss who did what in the last week. Then we start planning a new week in smaller groups. So we stay informed about the affairs of the whole team and work in tandem.
Working alone, you will waste time and effort in vain, increasing the number of tasks that you could overwise have avoid.

5. Do Analytics, Not Visualization

Don’t think that your work is only limited to data collection. Today, the human task, unlike a computer, is not just to collect and visualize information, but also to filter out all the unnecessary information. The charts won’t do all work themselves. Match the data, discard the unnecessary and look for dependencies that can find new growth points.

What data can be analyzed in Dashly?

You know that Dashly collects all information about the actions of visitors on your website. Based on this information, you can build funnels or even entire maps of customer paths.

Two of our largest analytical blocks are campaigns report and conversation report. Campaign report tells you how well you’re communicating with your customers in the chat. How to measure it more detailed we’ve said in our previous article.

The conversation report will help to determine how many times the email was sent, opened, answered, etc. Think about whether it’s all worth chasing after openings and clicks. Perhaps there are other, more important metrics? This is all detailed in another our article.

Apophenia (that is, a person’s ability to see the relationship in random and meaningless data) is not a new invention. At the same time, the propensity to confirm their point of view is also an existing distortion of human perception. In other words, if we simplify the dependencies, we will only see what we want to see.Taking into account all incoming information, we risk not making any conclusions at all. The secret, as always, in the search for the golden mean, the ability to cut off unnecessary and competent analysis of the available information.