Savvy brand marketers know more than anyone that powerful creative campaigns should merge data and emotions simultaneously. When it comes to display creatives, programmatic buying brings a lot more useful data into the equation.
Programmatic buying coupled with data-driven creative can deliver more effective digital advertising campaigns. However, it may be challenging to incorporate data within the creative brief due to the many stakeholders within a project. Here are a few suggestions on how to plan this type of campaign effectively:
When building a strategy, find what data is available and choose the right data signals from the most relevant channels. Take into account data from first-party websites, audience data used for planning contextual inputs such as device, location or media type and so on. Evaluate and make informed and smart decisions based on the information you collect.
Programmatic buying allows brands to use audience insights and technology to tailor messages to the right person, at the right moment, in the right context. For example, L’Oréal wanted to build a campaign to showcase two Vichy sunscreen products. One sunscreen was for women, and the other was for children. The challenge here was to create relevant ads for each segment, so the audience was divided into two lists: women with and without children. The data enabled the brand to target the right consumers at the right time.
Apart from making informed decisions about your audience, you should also involve each team that is working on a campaign strategy from the start. Through collaboration between production, media and creative stakeholders, the campaign will undoubtedly perform more successfully.
For example, Gilt wanted to create a campaign to show four merchandise categories. The top performing keywords supplied by Gilt were used by the production agency to produce ads tailoring each segment. Sharing these insights at the beginning of the campaign process enabled the production team to tailor their designs to each segment.
The data signal that was used was past top performing keywords of each audience segment from previous display campaigns. It was used to determine creatives, resulting in the male category products seeing an 80% increase in conversion compared to previous campaigns.
Through collaboration, the planning, analytics, creative teams and production team can maximise the results from the campaign. With use of data, smarter messages can be put across and tested appropriately.
The examples above show how campaigns can be successful in evaluating and adapting little tweaks from many stakeholders. The following guide to programmatic campaigns is extremely useful:
List out all data sources available and collect and segment appropriately to align with the business goal of the campaign. It will be helpful to make a checklist of user insights which will eventually act as inputs for the creative team to determine the messaging.
The three types of data signals that can be used to create a campaign are:
Demographic information such as gender, age, interests, and website analytics data such as previous pages visited, abandoned shopping cart rate etc.
User intent information such as keyword contextual targeting, app category etc.
The external factors that may influence customer mind-set when they see the ad such as device, operating system, location etc.
An extremely important part of a successful campaign is to align all stakeholders and bring them under one umbrella to run the data-driven campaign from start to finish. There are some important questions to be asked at this stage.
a. What are your brand’s overall goals for the campaign?
b. How do you segment your target audience, and what does each segment care about?
c. What data signals can be used to reach each audience segment?
d. What is the messaging for each segment?
e. What sort of creative might your audience respond to?
The data-driven approach begins with finding the data signals to align with the business goals. Choosing the data signals to work with is the starting point to defining metrics for measuring the campaigns. The metrics should be communicated across the various agencies involved. The data signals would also determine the messaging strategy.
The next process is to produce the creatives and test with a smaller budget. If there are multiple creatives don’t test all at once; instead test one or two together and follow with the other creatives in the next round.
The main challenge at this stage is to produce creatives that support various devices and websites. HTML5 designs are mostly suited for programmatic ads, ensuring all ads appear correctly on mobile devices and browsers. Google web designer is an excellent tool to create HTML5 ads.
Once the production agency produces the dynamic creative feeds, the media agency should set the feeds in the ad server or double click platform. All agencies should conduct a strategy map against the feed created in order to see if they are correctly set up. It is highly recommended to soft launch before the campaign is launched so that mistakes can be rectified and early learnings taken.
As the data starts gathering in the platform, the optimisation should start. This should begin with optimising the creative and targeting based on initial performance. Ensure the data is reliable and investigate any possible click frauds. Re-focus after the initial data is available and optimise the campaign to refine the best performing creatives. Work on strategies to maximise reach and satisfy the business goals set.
Data-driven programmatic buying offers significant improvement opportunities, but due to lack of inter-agency communication, the majority of the budget spent often goes to waste. This article provides a framework for when there are multiple agencies involved in the planning, creation and execution of a campaign.
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