Unfortunately, many companies that spend substantial resources storing and processing data still make important decisions based on intuition and their own expectations instead of data.
Why does that happen? Distrust of data is exacerbated by situations where data provides an answer that’s at odds with the expectations of the decision-maker. In addition, if someone has encountered errors in data or reports in the past, they’re inclined to favor intuition. This is understandable, as a decision made on the basis of incorrect data may throw you back rather than move you forward.
Imagine you have a multi-currency project. Your analyst has set up Google Analytics in one currency, and the marketer in charge of contextual advertising has set up cost importing into Google Analytics in another currency. As a result, you have an unrealistic return on ad spend (ROAS) in your advertising campaign reports. If you don’t notice this error in time, you may either disable profitable campaigns or increase the budget on loss-making ones. …
Never run paid advertising campaigns without preparing reports in advance so you can see the real efficiency of your investments. Wise marketers prepare report templates before running campaigns. Other marketers first waste their budgets, then still prepare reports in the end.
In this article, you’ll discover how to build reports easily, avoid extra manual work, and automate the entire process using the five most popular analytics software.
Advertising tables, charts, and dashboards are necessary for marketers to report the work they’ve done. But they have another important mission — helping with management decisions. …
If you’re like many marketers, you’re probably running campaigns using a variety of digital marketing channels — including not only Google Ads but also Facebook, Instagram, Twitter, LinkedIn, and many more. With no money to waste, you aim to get the most out of each marketing investment. And to do that, you need a clear, holistic view of your customers’ journeys across all channels and devices.
In this article, we’ll examine how you can get everything together and upload all marketing data into one data storage (e. g. …
Today, we’ll be interviewing Khrystyna Grynko, the Head of Data at the Better&Stronger web marketing agency.
Khrystyna is the DataCamp Lyon and MeasureCamp Lyon organizer and also serves as vice president at AADF (French-speaking Digital Analysts Association) and at TAAL (Technological Association for Advanced Learning).
In addition, she’s a guest lecturer at Jean Moulin University Lyon 3 and at Emlyon Business School.
According to Gartner, marketing analytics is the process of collecting, analyzing, modeling, and visualizing data to optimize marketing campaigns by better understanding users’ behavior across channels. Marketing analytics is also about measuring and optimizing marketing efforts. It helps you assess the impact of marketing on the business as a whole.
Thanks to marketing analytics, you can avoid guesswork and pay special attention to unprofitable marketing campaigns, uncover patterns and valuable insights into your marketing strategy, adjust your advertising campaigns, and get more revenue.
The importance of marketing analytics is illustrated by recent research by Gartner, Adage, and The Trade Desk.
There’s been a lot of talk about cookies and the fact that their lifespan will become much shorter than we’re used to. Let’s figure out what innovations await us and how marketers can adapt to the new reality.
2020 will be remembered not only by quarantine and the massive transition of the business to online. At the beginning of this year, Google announced its planned departure from working with third-party cookies. For newcomers to the industry, let’s clarify that third-party cookies are the crumbs of bread by which marketers know two things:
Building a good marketing strategy begins with data analysis. After all, you can’t improve anything without assessing its starting point. Luckily, you don’t have to do it manually — there are a bunch of specialized tools that can help you automate data analysis to save time.
In marketing, data analysis is the process of organizing, explaining, and interpreting data to answer questions regarding a marketing strategy, resolve issues with that strategy, and multiply its advantages. You might ask the following questions as the first part of data analysis:
To assess the efficiency of marketing campaigns, marketers use various metrics. Some are focused exclusively on expenses, others on revenue, and others on the return on marketing investment (ROI) — the ratio of revenue to expenses.
In this article, we discuss cost per lead (CPL) — one of the most useful and interesting performance indicators — and an advertising model based on it. Let’s take a look at how to calculate the cost of an attracted lead and see which businesses should do so.
The definition of CPL is a metric used to assess the efficiency of online marketing. It shows how much an advertiser pays to attract one lead on a particular advertising channel. …
In a world that survives the pandemic’s consequences, the game rules have changed for advertising. For obvious reasons, people began to use online shopping and solve household problems online more often than before. All this led to an increase in online advertising. According to Gartner, CMOs spend nearly one-quarter (22%) of the marketing budget on digital advertising.
Marketing directors can no longer afford to spend the budget to pay specialists to manually collect the necessary reports. In addition, reports are needed to quickly respond to changes, and when manually building reports, the speed is rather low. …
According to Gartner, about 74% of CMOs expect to spend more on digital advertising in 2021 than they did in 2020. But how can you assess your channels to know exactly where to invest more? Which ads make potential customers move to the next step of the funnel?
The solution is hidden in attribution — how the value of a conversion is distributed across channels that move the user through the funnel. However, some attribution models show you only part of the picture. And these gaps in data might be critical. After all, according to the rule of seven touches, the actual purchase frequently happens only at a customer’s eighth interaction with a brand. However, all steps affect one another and eventually lead to the conversion. …