Como você testa o conteúdo da sua campanha?

One of the simplest and most effective testing methods is A/B testing. In this approach, you create two versions of your content: the original (A) and a slightly different version (B) with a single variable changed. For example, you could test two different headlines to see which one resonates better with your audience.

When promoting an advertising campaign, it is important to determine what exactly to test, such as design, text, unique value proposition, or the Call to Action, and so on. Based on the answer to the previous question, we formulate hypotheses. Subsequently, we test these hypotheses using various popular testing methodologies and evaluate the results.

I would create 4-6 versions of the same ad, i.e. a video, but change up the "HOOK" on each of theme to reflect a different angle, such as different problems the product or service solves. This is a quick way to test that doesn't require a ton of extra video editing, as the video stays the same. Then scale the winner. It's important to often change up your ads especially on Meta nowadays, only few ads do well over a longer period, so you do need to invest in new content creation and UGC.

Testing email campaign content is the backbone of successful email marketing. I personally endorse A/B Testing FTW. Splitting my audience and testing variations is a game-changer. Subject lines, sender names, visuals, CTAs – every element gets tested. This data-driven approach tells me what resonates best, leading to higher open rates and click-throughs.

Ideally you should place a pixel on the page where you would be putting the content with UTM parameters to measure how it's performing especially Average Page View Duration (should be more than 66 sec). Once you have the data then you can start A/B test your headlines that matches with your content and visuals could be realistic, sometimes opposite to what your content belongs so it attracts the users.

Since I always try to make data-driven decisions, the best way would be to AB test (AKA Split Testing). You define your hypothesis, the KPIs, and the sample size needed to achieve the conclusions and test. - The correct way to get "clean data" is to only change one variable in your B variant so there will be no other interferences. - The KPIs vary from test to test, business modules and campaign goals. Always test before launch! Good luck.

I employ two proven methodologies to achieve valuable results in campaign content optimization: A/B Testing: A widely recognized and effective approach to content testing. However, for businesses operating with smaller databases, attaining conclusive results can be challenging due to limited sample sizes. Tagging and Grouping Campaign Types & Segments: Within your content strategy, it's crucial to categorize each campaign based on attributes like campaign type, discount type, etc. For instance, if your business frequently conducts product launches, discerning which customer segments interact with specific content is pivotal for refining your product launch strategy.

The two testing goals I like to consider is Enhance Engagement: Measuring metrics like time spent on the page, shares, likes, and comments can help assess how engaging your content is for your audience. Improve Brand Awareness: Testing can help you gauge whether your content is effectively spreading awareness about your brand, product, or service. Similarly, for testing metrics, I consider the same, Engagement Metrics: These include likes, shares, comments, and time spent on the page. They indicate how well your content is capturing and holding your audience's attention. Brand Lift: A survey-based metric that measures changes in brand awareness and perception before and after exposure to your content.

I use the following metrics as a minimun in marketing and evaluate them within one marketing campaign scope: Web Promotion: Number of leads, Number of activations, Conversion rate for funnels, Number of transactions Mobile Promotion: Number of installations, Number of registrations, Conversion rate for funnels, Number of transactions, Number of purchases, Number of valuable actions, Churn Rate These metrics allow me to assess the effectiveness of marketing efforts depending on the type of promotion and assist in the analysis and optimization of campaigns.

For video, watch time is gold. The longer you can captivate a viewer the more likely your ad resonates and sticks with them. You can then retarget the people who watched the longest with a different ad that is more focused on direct conversions.

Enhance Engagement Testing: Goal: Increase interaction and interest in content. Variations: Test headlines, visuals, CTA buttons, content length. Metrics: Measure time spent, comments, shares, likes, scroll depth. Improve Brand Awareness Testing: Goal: Boost brand visibility and recognition. Variations: Test brand messaging, visual consistency, storytelling, influencer collaboration. Metrics: Monitor brand searches, social mentions, recall, traffic sources. Testing these variations and tracking corresponding metrics provides valuable insights for impactful content strategies.

Test for Mobile App Call To Action (CTA) using Acquisition Rate: Goal: Increase app downloads through the CTA. Create Variations: Make different versions of the CTA (e.g., "Download Now" vs. "Get Started"). A/B Testing: Randomly show variations to user groups. Measure: Track views, clicks, and downloads for each variation. Analyze: Calculate Acquisition Rate (downloads divided by clicks) for each CTA. Determine Winner: Select the CTA with the higher Acquisition Rate. Implementation: Use the winning CTA in your app. Continuous Optimization: Regularly test and refine CTAs for better results.

Enhance Engagement Testing: Time Spent: Longer average time on page indicates better engagement. Comments and Shares: More comments and shares show content is engaging and shareable. Likes and Reactions: Higher likes and reactions signal positive audience response. Scroll Depth: Deeper scroll suggests user interest in content. Improve Brand Awareness Testing: Brand Searches: Increased brand searches reflect raised curiosity. Social Mentions: More mentions and tags enhance brand visibility. Brand Recall: Higher recall rates imprint brand in users' minds. Traffic Sources: Analyze traffic origin for effective brand awareness.

I use in-app or web analytics tools to gather data and measure key metrics such as Activation Rate, Churn Rate, and Retention Rate not only for campaign testing

Apart from above mentioned strategies, you would also want to test it with at least 2-3 different platforms and not relaying on only one where users behaviour or analyzing method is similar, you would always want variety of audience to be tested to get better results.

Based on conducted tests, a mathematical forecast is calculated. This forecast is intended to predict the campaign's performance when scaled up. If the forecast does not show good results, either the testing is repeated, or additional data is collected for analysis in search of insights that may have influenced the outcome. This process allows for strategy adjustments and improvements in campaign effectiveness.

In conclusion, testing content variations is an indispensable strategy for achieving enhanced engagement and improved brand awareness. By meticulously analyzing metrics such as time spent, comments, shares, likes, reactions, scroll depth, brand searches, social mentions, brand recall, and traffic sources, marketers gain valuable insights. These insights drive informed decisions, allowing refinement of content strategies that cater to audience preferences and elevate brand recognition. Effective testing transforms data into actionable steps, leading to content that captivates audiences and fortifies brand presence in the dynamic landscape of digital marketing.

We should remember that testing isn't a one-time thing. Consistent iteration based on results is what elevates email campaigns to their full potential.

If my goal was properly set, the numbers will be meaningful for the advertiser. If that isn't the case, metrics can dissapoint the funding source. For example, the main stakeholder can be interested in revenue over impressions, subscriptions, or clicks. So, if you're hesitant about your performance indicators, runnig tests prior to launch aggresive campaigns is better. If you only got one shot, focus on the initial research and the creatives, the rest is an outcome from previous efforts. So, spending over 60% before launching the campaign itself will pay the price. And last but not least, the simpler the better. Find 5 metrics that balance each other. Improve e.g. Conversions, CTR, CPA, ROAS, and Bounced (could be abandonned-carts).

Segmentation i believe is the key element. Through segmentation one can easily analyze the taste , interest as well as the weak portions.

Segmentation is Key. Before anything else, I ensure the content is tailored to the specific audience segment. Generic content rarely hits the mark. Understanding the preferences, pain points, and interests of each segment helps in crafting more engaging messages.

I think a lot of money and time can be wasted on A/B testing. The best option I have found is to simply run the campaigns and analyse after how they performed.

Don't forget to continuously refine your campaign content through iterative testing and refinement. There should be a cooling period where you watch for your TA's reactions to the campaigns, but once you start to see results then start to act. Don't be afraid to test new variations, and make adjustments based on insights, this will ensure you continue to improve the performance of your campaign over time. By following this systematic approach, you can test and optimize your digital campaign content to achieve your desired objectives and drive successful outcomes.