Guest post was prepared by Roman Onishchuk, head of product and marketing strategy at Proofy. Proofy is the largest bulk email verification service in the USA. The company gets an award #4 Product of the day on Product hunt platform and also was distinguished with Premium Usability and Rising Star awards from FinancesOnline.
Managers and business owners sometimes consider analytics to be multi-volume, boring reading with a bunch of incomprehensible tables, graphs, and figures. Small reports, statistics extracts, and similar stuff is not marketing analytics, especially in digital.
Everything starts with the fact there is no sense in the analysis without referencing it to some specific and measurable goals. Not to mischief, it’s better to start with simple and clear steps. Then you can create complex systems, diagrams, segments and use super-complex tools.
What is a marketing analytics and why to use it?
It’s better to start the analysis with the definition of key indicators and the links between them. This is not about setting goals in Google Analytics, but about the systematic approach which:
1. Provides clear answers to specific business questions
2. Finds solutions rather than stating facts from the past as a report.
Can we just generate automatics reports or quickly make decisions on the results of the A/B test? Or do we need difficulties like abstruse systems and connections? Let’s investigate the example.
Jennifer owns a small but quite popular beauty salon in her area. There are no bookings for a couple of months in advance, so she periodically arranges advertising activities. But she doesn’t want to waste her money, so she analyzes her email (not forgetting to perform a free email validation), Instagram and Facebook advertising campaigns. We are sure entrepreneurs do so, as we always perform marketing campaign analysis at Proofy.io.
Running 2 identical ads, Jennifer decides to compare the 2 banners. The first one she did by herself using a free mobile app from the App Store, and the second one was prepared by a professional designer for a significant payment. A week passes, Jennifer compares the results.
|Self-made free banner||Expensive designer’s banner|
|120 calls||180 calls|
|22 appointments||34 appointments|
These numbers show her an obvious choice – the expensive banner justifies itself, more calls, more appointments. Isn’t that so?
But if we dig deeper, it can be quite superficial. But here are several possible nuances:
- The average check from an expensive banner can be much lower than from the cheap one. In the end, there will be more money brought by a self-made promotion.
- In the long term, it may occur that customers who clicked the cheap banner return 3 times on average. And the ones who came from the designer’s banner come only once because of the overestimated expectations.
- Some customers may find banners in the emails annoying and report them as spam. Bulk email validation might help you in this case.
So here’s an obvious and simple conclusion: it is necessary to analyze different indicators and dig deeper. It’s better to look wider into the bright future, with the mom goggles taken off.
Key principles of correct marketing analysis
The main analysis tasks are to solve a specific problem, eliminate the business pain, and provide recommendations for development. In Proofy.io we always try to base it on specific principles.
Objectivity and flexibility
We need to find the data that directly affects the problem, and look at them from different angles. Of course, the director’s and managers’ personal opinions are important, but numbers stand for themselves.
We don’t need analysis because that’s what competitors do, because that’s what we heard at the training, or because it’s just the way it’s supposed to be. The analysis is needed to solve specific problems, so we should define the real “pain points”.
Proper problem statement
The more specifically we describe a task, the more useful analysis we may expect. A kind of a blurry request like “I want all the metrics to grow at once” is doomed to failure. And here’s another example of the problem formulation: “the goal is to reduce the marketing costs by 10% with minimal decrease in sales”. See the difference?
In the second case, an analyst may identify ineffective channels, irrelevant audience segments and find the potential for improving the existing campaigns.
Marketing Analytics both in digital or offline business should not be perceived as an ancient cuneiform. Even a technically untrained person should easily understand the analysis results. This is a fundamental difference from reports, which give you hundreds of pages, graphs and incomprehensible diagrams.
These principles will form the basis. But pursuing metrics and databases, we can fall into the trap of measuring everything and considering it as something normal.
Why not measure everything at once
After all, we can reduce all the complex measures to simple metrics:
- users’ moves;
- brand mentions in reputable sources;
- actions at different stages of the sales funnel.
The key problem is we can’t know everything about our users at once. Arguments:
- We can’t track potential clients’ actions on different devices if there is no synchronization between social networks and email etc. After all, the buyer can see the beauty salon advertising on his iPad, then drive a brand request (the name of the salon) in Google and forget about it. And then, a month later, having a 2 hours gap between classes, come and get a haircut.
- We can’t track real-time brand awareness (e.g. publishing useful content for you guys and mentioning Proofy.io and email verification inside). Yes, it improves conversion, forms loyalty, increases the average check and even can create demand for new services. But this we can only understand in the future, after a careful marketing campaign.
- We can’t predict the results of users’ cognitive biases. E.g. when we set a specific goal and create a binding effect. Sometimes these bindings are positive and sometimes they are not. For example, you say “we have a promotion when ordering a haircut — super-styling for the price you set yourself.” And add: “for example, $10, $15, $20”. Despite its real cost can be only $6, people are more likely to pay at least $10. The same way with promotions and discounts: “I don’t need that suitcase, I came for the iron. But damn, it’s only worth $200 now, not $600, I’m saving $400.”
- We can’t know everything about our users, and we don’t need to. Most often it’s enough to understand the results of “before” and “after” to assess the actions’ correctness. The main thing is to remember the goals and specific problems that we solve. Therefore, in most cases using simple and accessible tools is enough.
A marketing analytics checklist for your company
Now it’s time to check how it all coincides with your company’s reality. If something is wrong — don’t worry, now you know what should be fixed.
- Google Analytics, Facebook Pixel, and other analytical tools are connected to the website and gather information.
- The goals for different events are configured — not only “bought” and “ordered”, but also the other funnel stages – “downloaded a free product”, “subscribed”, “ordered a call back”.
- The UTM tags for different advertising campaigns and ads are set to understand the effectiveness of each advertising channel.
- The specific goals for marketing analytics are defined — to reduce costs, to optimize advertising, to increase the average check, etc.
- The analytics often looks like a routine ― many everyday tasks that, with a reasonable approach, help in lead generation, cost optimization, and sales increase. But it is a “must-have” for those who want noticeable business growth.