Voici comment vous pouvez démêler les raisons d’un échec marketing grâce à l’analyse et à l’interprétation des données.

Yes, a data audit can reveal if the campaign missed capturing any data required for analysis. It can also help you understand the quality of the data captured. For example, if we put a banner on our website below the fold section and the click through rates are very low even if the the number of impressions are very high, there could be an issue with how we're capturing impressions. If impressions are counted at the time of page load, then there's a problem. Impressions should only be counted if the visitor actually sees the advertisement—that is, if the advertisement is in the visitor's viewport for a minimum amount of time.

The goal of marketing is to expand audiences, but are they qualified and engaged? From FMCGs to luxury items, engagement levels vary. Effective marketing should spark inquiries, even without immediate purchases. For FMCGs, brand recognition testing is essential—always include a control group for accurate results. Luxury brands must assess how many qualified prospects can afford them. Data analysis reveals if campaigns reach the right audience, focusing resources on attracting engaged prospects. Understanding consumer behavior through data refines marketing strategies, making campaigns more efficient and impactful. Treat marketing like an science experiment with empirical evidence for best results.

Please look at the data from the start of your campaign until the end, and make sure you can stitch all your campaign data from various sources into one view. Here is a scenario, you created a landing page to attract conversion, ran a couple of ads on platforms like Google and social media platforms like Meta and Instagram, etc, created a bunch of social organic posts, created some email campaigns, sent WhatsApp blasts, SMS, and PR campaigns. You ran 360 marketing campaigns across all channels. The data is scattered into different sources and you need to make sure you create a single view to analyze the data, meaning you need to audit all sources for accuracy and credibility.

The main thing is that all these indicators and metrics do not distract from the main goal - revenue growth and company profit :-)

Compreender e utilizar KPIs é fundamental para o sucesso de qualquer campanha de marketing. Ao colaborar com especialistas e analisar os dados corretamente, você pode garantir que suas estratégias estejam sempre alinhadas com seus objetivos e estejam gerando os resultados desejados.

You need metrics and KPIs to define either the success /failure of your campaign. The identification of correct KPIs and metrics is a key component in the analysis process to determine failure / success of your campaigns.

You should check for anomalies in trends whether it drop in traffic, conversion, impression, etc, also keep an eye on your competitions whether your competitors are affected by downtrend due to the external economic factors or it's just you

Even your failed campaign might have worked for a cohort of users however insignificant the overall contribution of these users in total revenue.No way I am saying it's a silver lining but the practice of segmenting users in cohorts based on behaviour can tell a lot about your campaign performance for these different types of users.

This is where the real detective work happens. It is tempting to jump into conclusions, but it's important to follow a proper method. Start with the most likely explanations and work your way down. Once, we thought our Ad wasn't performing well due to poor targeting, but after some digging, we found out that its happening because of ad fatigue. The ad frequency was too high. A useful trick is to also test the opposite of your hypothesis.

Teste de Hipóteses em Marketing: Transformando Suposições em Evidências Ao adotar uma abordagem estruturada e baseada em dados, você pode transformar suposições em insights acionáveis, levando a estratégias de marketing mais eficazes.

Testing a hypothesis is a critical step in defining the campaign's objective. The hypothesis is nothing but a statement that data can accept or reject. Having a clear hypothesis for your campaign is critical and if it fails then it means your hypothesis to start was completely off and perhaps next time more thought and efforts need to be given to define clear objectives and goals

While data provides valuable insights, misinterpretation can lead to misguided decisions. Common mistakes include: - Overemphasizing metrics like CTR and conversion, without considering broader context and algorithms. - Misinterpreting growth percentages, which may appear impressive on the surface but lack scalability and viability. - Ignoring attribution and references, leading to incomplete understanding. To avoid these pitfalls, marketers must: - Take a holistic approach to data analysis. - Consider multiple metrics and contexts. - Seek to understand the story behind the numbers. - Continuously refine their understanding of data and algorithms. By doing so, digital marketers can make informed decisions that drive meaningful results.