For marketers, a primary goal is to maximize marketing ROI by ensuring marketing spend produces the best results. This means sending campaigns to the right people, at the right time, with the right message. But how can you know what’s right?
In this post, we look at how to take the guesswork out of marketing campaign success by leaning into data-driven campaigns with a scientific approach to campaign design.
Whether you are working to acquire new customers or looking to engage existing customers, your best path to success involves research and testing. No matter how much or how little runway you have in the lead up to your campaign, you should be able to accommodate one, or even all four, of these data-driven approaches:
- Pre-campaign market research. Market research can uncover preferences and emotional drivers that you can use to inform which channels and messages will have the best likelihood of success.
- Pilot test. Pilot testing allows you to test a variety of variables with a small number of targets before you run your full campaign. Following your test, you apply learnings from your pilot to the full campaign. Although this is an additional step in your campaign, you may discover it provides the most direct path to achieving your objectives.
- Test within a campaign. If you do not have time for market research or a pilot test, you can still generate customer insights by setting up your campaign in an experimental way. This will yield learnings that can be applied to future campaigns.
- Post-campaign market research. Surveying targets following a campaign can produce insights into why targets did or did not respond. If the goal of the campaign is to get a recipient to buy, enroll, or otherwise respond, you can learn what motivated them to act or not.
How to Set Up Campaigns in an Experimental Way
Start by developing a hypothesis. According to growth marketing strategist Chris Goward, “A well-structured hypothesis provides insights whether it is proved, disproved or results are inconclusive.” An example of a simple hypothesis might be: “Customers will respond at a higher rate to our new creative design, than they did to last year’s creative design.”
A/B testing is a way to compare two or more versions of your marketing material to figure out which performs better. You can also A/B test two different target markets to help answer questions like, “Will customers who already have product X adopt product Y, and will they do so at a higher rate than those that don’t?”
Define the Target Audience
Some experts believe campaign success depends 70% on who you’re targeting and 30% on messaging and creative. So, getting the target list right is crucial.
Choose the Marketing Channels
When considering the best marketing channels for your campaign, do you know with confidence which channels are the most effective? What success have you experienced with your current channels? If you can’t adequately answer these questions, you may want to consider running a pilot test that offers insights into which channels your targets are most likely to respond to. If you find yourself with an absence of empirical data to determine the right channels for your campaign, don’t be afraid to make some inferences, based on theoretical deductions or hypotheses you may have.
Develop the Right Message
Developing marketing messages that speak to your target requires an understanding of emotional drivers. Simply knowing what messages have worked or not worked in the past can help you refine your message as you advance to your next campaign, and eliminate the need to test messages you already know are not going to work.
Develop the Creative
Your marketing creative – the artwork, design and imagery that is the basis for your marketing content or materials – should also be viewed through a scientific lens. Applying a scientific approach to the creative for your campaign is similar to how you develop the right message. You’ll want to research emotional drivers and make sure your creative is on brand.
Develop the Offer
Pre-campaign market research is exceptionally helpful in determining your offer. You can develop confidence in your offer by conducting a conjoint analysis, or trade-off analysis, prior to your campaign. For this analysis, you survey your targets about a choice of products or options. To determine market potential, ask customers to choose between two or more different products, or between similar products with different feature sets. Be sure to include a “none” option to ensure your analysis reliably reflects the preferences of respondents.
Another way to refine your offer is by conducting a principal component analysis (PCA). A PCA can help you understand which of your products cluster together based on customer buying behavior and demographics.
Consider Campaign Execution
If you’re managing marketing in a distributed organization, extend your data-driven design to campaign execution. Slight variations in campaign execution encompass a wide range of factors and impacts, from campaign control, target market reach, customization, localization and local relevance, to technology capabilities, budget and responsibility for costs. By taking the time to consider these factors, you can determine how they may help or hinder you in addressing your campaign objectives. Read more here: 5 Ways to Structure Campaign Execution for Distributed Marketing.
To learn from your experimental design, you will need to be able to accurately measure the campaign results. This requires up-front planning on how and what to track.
- Start at the End. Campaign tracking – whether it’s for a pilot test or a full campaign – is one of those marketing disciplines that needs to be thought about and designed at the beginning of a campaign.
- Map the Journey & Track All Channels. Prepare to track campaign results by anticipating the channels your audience will use to respond. The method of campaign tracking you use depends on both the medium used to engage your targets, and the channel they’ll use to respond.
- Allow Time for Results to Develop. Be careful about reporting or looking at results too soon. Before you begin analyzing the results of your pilot test or campaign, understand your response curve. You might expect to see half (50%) of responses come in the first week, 20% in the second week. So, it’s important to allow sufficient time for responses to be received before drawing any conclusions. Aim to collect 90% of responses before you start analyzing.
Results Analysis for Optimization
Using your experimental design as a guide, analyze performance of key dimensions of your campaign: targets, channels, messages, creative and offers. If direct mail is working better than email, look closer at the respondent profiles. You will discover there’s rich information and insights from all channels that can help inform your next campaign.
Capture & Apply Learnings
After completing your analysis, bring it all together into a set of recommendations. If you’ve conducted a pilot, apply what you’ve learned to the primary campaign. If you’ve run the full campaign with experimental design built in, apply your analysis to your next campaign.
Data-driven marketing success requires a scientific approach. Embrace experimental design as an ongoing discipline that will yield progressively greater insights and results for your data-driven marketing campaigns.
Learn more about data-driven marketing campaigns in the Vya eBook, Data-Driven Campaign Design: A Scientific Approach to Maximizing Campaign Results. This eBook is intended to guide marketers through a journey of increasing customer understanding and engagement – beginning with experimental campaign design, tracking and analysis, and progressing to an ongoing process of applying learnings to future campaigns.
Download the eBook here.