{"id":5415,"date":"2024-07-08T12:36:00","date_gmt":"2024-07-08T10:36:00","guid":{"rendered":"https:\/\/yetiz.dev.yetiz.pl\/5-powodow-dla-ktorych-twoja-firma-potrzebuje-skonsolidowanych-danych-marketingowych\/"},"modified":"2024-11-27T12:40:10","modified_gmt":"2024-11-27T11:40:10","slug":"5-reasons-why-your-company-needs-consolidated-marketing-data","status":"publish","type":"post","link":"https:\/\/yetiz.dev.yetiz.pl\/en\/5-reasons-why-your-company-needs-consolidated-marketing-data\/","title":{"rendered":"5 reasons why your company needs consolidated marketing data"},"content":{"rendered":"\n
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Where Are These Conversions Coming From?<\/h2>\n

Using multiple tools in campaigns, and thus various metrics and attribution models, makes it difficult to quickly and easily determine what (and to what extent) impacts the final outcome. The Customer Journey only complicates things further. Why? The customer first needs to discover us (one set of metrics), engage (another set of metrics), make a purchase, and ideally, return and recommend us to others (yet another set of metrics). At each of these stages, we use tools with different indicators, and these tools influence each other. Additionally, many of the actions we take have delayed effects\u2026 So, what ultimately \u201edelivers\u201d the result, and to what extent?<\/p>\n

Even if you manage to align everything to one tool\u2019s metric, you still often can\u2019t directly compare the data. Just compare conversion data from Meta Ads and Google Ads\u2014when you sum them up, you should already be counting proverbial millions. But somehow, that usually doesn\u2019t happen. It turns out that platforms can attribute the same conversions to themselves (even in last-click attribution).<\/p>\n

Is it worth it? This question comes up often, and the answer is always: yes, because data brings you closer to the truth about what works and what doesn\u2019t.<\/p>\n

Parallel Worlds<\/h2>\n

Sometimes I feel that marketing functions in companies as a department that no one understands. Management boards or sales departments don\u2019t really know what marketing does. And they don\u2019t seem to want to know, let alone understand. They perceive marketing as a kind of black box into which you pour a budget and later expect results. And it\u2019s usually the first budget to be cut during a crisis (often a self-defeating move). On the other hand, marketing usually doesn\u2019t feel the need to explain its actions or results. When asked, \u201eWhat exactly do you do?\u201d they respond with, \u201eDon\u2019t worry about it.\u201d<\/p>\n

This also extends to the collaboration between marketing departments and agencies. The expectations expressed by the marketing department and what the agency understands and delivers can sometimes be like proverbial parallel worlds. A recent example: the goal set for an agency handling a tool was to increase overall brand sales. The agency\u2019s approach: squeezing the maximum ROAS at the expense of cannibalizing other channels. The tool\u2019s reports look green. The company\u2019s sales goals are not met. What went wrong?<\/p>\n

Another case: the goal of the activities is to acquire customers with the highest possible repeatability, meaning customers who can be monetized over months. Every year, the company spends significant amounts on Black Friday campaigns, despite the fact that customers acquired this way are exceptionally disloyal. But the first sale conversion metrics look great. The reports from individual tools also look good. The only problem is that the customer doesn\u2019t come back.<\/p>\n

What if we communicated with the agency based on business metrics, which the agency could then translate into goals for individual campaigns?<\/p>\n

At one point, Bartek Pucek, in one of his newsletters, used an analogy that stuck with me. We should not only do more things that allow us to accelerate but, more importantly, do more things that accelerate us in the right direction.<\/p>\n

The English language has two distinct terms for this: speed and velocity.<\/p>\n

A\/B Testing as a More Effective Form of Optimization<\/h2>\n

An experiment that demonstrated that iterative improvement leads to better results than trying to create a perfect project from the start was conducted by Peter Skillman and is known as the \u201eMarshmallow Challenge.\u201d<\/p>\n

Teams that tried to meticulously plan and create the perfect project from the beginning often did not achieve good results, or the tower collapsed under the weight of the marshmallow.<\/p>\n

Teams that adopted an iterative approach\u2014building, testing, improving, and then building again\u2014achieved significantly better results.<\/p>\n

The problem is that modern marketing is more than just one type of marshmallow. Effective campaigns use a multitude of tools. You could compare it to a symphony orchestra, with marketers as conductors who orchestrate the performance.<\/p>\n

Orchestration means arranging a musical composition for different instruments in the orchestra. The composer or arranger decides which instruments will play specific parts of the composition to achieve the desired sound effect. The conductor relies on their ear (ideally absolute pitch), while the marketer relies on data analysis. With a consolidated analytical model, we input the changed values from individual tools and observe the final marketing effect and its impact on business results.<\/p>\n

Zero-Party and First-Party Data as a Competitive Advantage<\/h2>\n

In the new reality (GDPR, consent mode, etc.), it has become clear that nothing improves campaign efficiency as much as having your own data collection. In other words, more data.<\/p>\n

Often, we use this data to segment customers and conduct personalized communication. But which segments should we focus on, which traffic is more profitable than the rest, which part of the funnel is worth investing more in, and which data should we focus on collecting? These are questions worth asking, but many marketers don\u2019t. The answer to them lies in a model that integrates metrics from top to bottom: from business metrics to impressions in individual tools.<\/p>\n

Then, data (and skilled analysis and inference) can become a real competitive advantage.<\/p>\n

Market No Longer Works for Marketers<\/h2>\n

The complexity of data (where are the days when you could make a media plan in Excel!) surpasses our cognitive capabilities. The language and data we use are becoming increasingly abstract to others. In all this, AI is increasingly supporting us (and that\u2019s a good thing). But the development of artificial intelligence also comes at a price for the industry, which can be summed up in one sentence:<\/p>\n

AI is displacing, and will increasingly displace, people involved in the configuration and optimization of individual tools. This is already happening.<\/p>\n

Optimal tool configuration will become the floor, not the ceiling. Everyone will have easy access to this knowledge, and it will cease to be a competitive advantage. Just a few clicks will be enough to have a tool optimally configured with AI assistance.<\/p>\n

The winners (or perhaps survivors) will be those who can effectively combine tools (various ones) with human behaviors\u2014something AI cannot do, at least for now. They will have a broader perspective. And an integrated data model can significantly help with that.<\/p>\n

Key Takeaways<\/h2>\n

These are just some of the reasons why it\u2019s worth collecting and consolidating data now. If you feel like this is also \u201eyour problem,\u201d it\u2019s high time to start building an analytical model that will make it easier (though not easy) to pinpoint the impact of individual tools and actions on overall results, not just in marketing but also in their impact on company performance.<\/p>\n

\u2013 Using multiple tools and metrics makes it difficult to determine what influences results (marketing or business). Inconsistent data can lead to incorrect conclusions. The solution (though still imperfect) is to create an analytical model.
\nA lack of understanding of marketing activities by other departments and misunderstandings between marketing departments and agencies often lead to ineffective actions. These actions may look good in reports but don\u2019t support key business goals\u2014often due to inconsistent metrics.
\nIterative testing and improving campaigns yield better results than trying to create the perfect project right away. Therefore, it\u2019s worth testing, collecting data, and using it for optimization.
\nCollecting and analyzing your own data allows for better customer segmentation and more effective campaigns. Data, in other words, knowledge, can become a competitive advantage.
\nThe growing role of AI in marketing means that optimal tool configuration is becoming standard, and companies that effectively combine tools with knowledge of human behavior will gain the advantage.
\n\u2013 Consolidating marketing data from various sources allows for a better understanding of the impact of individual activities on overall company results and makes it easier to make informed strategic decisions.
\nWhere to start? How to simplify your work in this area? That\u2019s a topic for another post \ud83d\ude42<\/p>\n <\/div>\n <\/div>\n <\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

In marketing, especially digital marketing, we use dozens of tools, metrics, and messages. Each of them provides a lot of data that is difficult to compare, and bringing them to a common denominator (to make comparison even possible) requires a lot of time, effort, and certain compromises. If we add company results (such as sales, profitability, or resource coverage) on top of that, and not just strictly marketing metrics, the picture becomes even more complicated. But why is it worth making this effort? Here are 5 reasons!<\/p>\n","protected":false},"author":19,"featured_media":4891,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1187],"tags":[],"class_list":["post-5415","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-account-based-marketing-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/posts\/5415","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/comments?post=5415"}],"version-history":[{"count":2,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/posts\/5415\/revisions"}],"predecessor-version":[{"id":5551,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/posts\/5415\/revisions\/5551"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/media\/4891"}],"wp:attachment":[{"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/media?parent=5415"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/categories?post=5415"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/yetiz.dev.yetiz.pl\/en\/wp-json\/wp\/v2\/tags?post=5415"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}