Today’s marketers have more opportunities than ever to capture consumers’ attention. However, the more opportunities marketers pursue, the more difficult it becomes to understand which campaigns are efficiently driving sales and which are lagging behind.
The three methods of advanced marketing measurement – incrementality testing, data-driven attribution, and media mix modeling – offer a sophisticated approach to evaluating how each marketing dollar you spend contributes to your overall success.
In this post, we’ll explore these fundamental techniques of advanced marketing measurement, discuss why each is important, and describe when and how they can be successfully applied to channels like programmatic marketing.
What is Advanced Marketing Measurement?
Advanced marketing measurement goes beyond traditional methods to provide a comprehensive view of how various marketing channels influence customer behavior and business outcomes.
Unlike last-touch measurement, which attributes a sale or conversion to the last point of contact, advanced measurement considers the entire customer journey.
This holistic approach captures the influence of non-marketing drivers, including competitors’ efforts, changes in demand, seasonality, and pricing and promotion. It also accounts for interactions between marketing channels, offering a more accurate assessment of their impact.
The Difference from Last-Touch Measurement
The advent of UTM parameters, pixels, and cookies has made it relatively straightforward to measure digital marketing campaigns on a last-touch basis. However, the answers that last-touch measurement gives can be misleading.
Last-touch attribution ignores the impact of any other touchpoints that contribute to a conversion. This can be a problem for brands using two or more campaigns to drive volume – especially when consumers typically see ads from more than one on their journey to purchase.
In addition, a subset of sales often cannot be linked back to an advertising campaign. Whether this is due to improper configuration, direct searches based on word of mouth, or another factor can lead to contentious conversations.
Advanced measurement quantifies the effect of all interactions, recognizing that channels like social media, email marketing, and programmatic advertising play a part in driving conversions and showing the impact of non-marketing variables. This helps distinguish between and give appropriate credit to both demand capture (converting existing interest) and demand generation (creating new interest).
Why Use Advanced Marketing Measurement?
The benefits of advanced marketing measurement, compared to last-touch attribution or marketing based on “gut feel,” fall into three broad categories.
- Accuracy: Provides a clearer picture of each channel’s performance, which helps marketers make better decisions while planning their budgets and executing against existing plans—no double-counting of sales numbers or disagreement over which campaign drove which sale.
- Optimization: Advanced marketing measurement shows how to allocate budget across multiple channels, minimize CPA, and maximize sales. Marketing teams using advanced measurement are less likely to overpromise and underdeliver because their forecasts account for the influence of non-marketing factors on their sales targets.
- Strategy: Forms a feedback loop with decision-makers by revealing insights about customer behavior and preferences while providing opportunities to test tactics before inclusion in a long-term strategy.
Methods for Advanced Marketing Measurement
Advanced marketing measurement depends on three key methodologies:
- Marketing Mix Modeling (MMM) is a set of high-level, statistical approaches aimed at correlating marketing activity with sales. It quantifies the impact of media performance alongside pricing, promotion, seasonality, competitor data, and a host of other external factors. It does not require user-level data. MMM is especially valuable for determining proper budget allocation, scenario planning, and forecasting.
- Incrementality Testing determines the impact of marketing campaigns on consumer behavior by comparing the purchasing history of audiences exposed to specific marketing assets against those that were not. When properly designed, these experiments implicitly control for the effect of non-marketing factors. It is the gold standard for detecting causal relationships between marketing and sales and a great way to assess new campaigns and channels.
- Data-Driven Attribution (DDA): DDA assigns credit via user-selected algorithms to digital touchpoints tracked along the path to conversion. It is relatively quick and easy to scale. Once integrated into marketing systems, DDA returns ongoing results in real-time and enables sophisticated bidding and optimization. It is useful as an operational tool for managing active campaigns.
Practical Example
Consider a scenario in which a company relies on email marketing and programmatic advertising. Results from MMM and DDA show that both channels generate sales but in very different ways. DDA highlights the effectiveness of lower-funnel email campaigns in converting consumer interest into sales, while MMM shows that programmatic ads create the interest that emails capture.
The company decides to verify these results by running an incrementality test. They find an easily distinguishable segment of their audience and exclude them from programmatic campaigns for a month. When compared to audience segments that saw programmatic ads during the test, this holdout group shows a lower rate of email opens, clicks, and purchases, attesting to the value those ads bring.
Given the support their incrementality test lends to results from MMM and DDA, the company decided to continue in both channels and explore options for growing the demand-generation portion of their budget.
If you want to learn more about advanced marketing measurement, including how it can help your business, visit tapindigital.com and schedule a free consultation.
The Role of Programmatic Marketing
What is Programmatic Marketing?
Programmatic marketing involves the automated buying and selling of online advertising. It uses data and algorithms to deliver ads to the right people at the right time, ensuring efficiency and precision. Examples of the types of ads you run for programmatic are display banners, video, connected TV, and native ads. This type of marketing is particularly effective for generating awareness and driving demand.
Why Advanced Measurement is Essential for Programmatic Marketing
Programmatic marketing’s primary purpose is to create awareness and attract potential customers, making it difficult to measure using last-touch attribution. Advanced measurement techniques, such as media mix modeling and incrementality testing, are crucial for understanding the true value of programmatic ads within the broader marketing mix. These methods show how programmatic ads contribute to overall brand awareness and subsequent conversions, even if they aren’t the final touchpoint.
Real-World Examples
In our experience at Tap In Digital, advanced measurement with media mix modeling has highlighted the importance of programmatic marketing in various campaigns. For instance, a client of ours tried to measure the impact of their programmatic marketing using last-touch attribution. The results showed a high last-touch acquisition cost, which led to their CMO asking that these campaigns be turned off because it looked like wasted marketing spend. This is a common occurrence we encountered during our experience at Tap In Digital.
The client reached out to us about our advanced measurement solutions. We explained that we take a holistic approach with our media mix modeling and determine attribution with advanced analytics vs. using any specific attribution method like last touch, etc. After collecting the data and running our media mix modeling, we found that, historically, programmatic marketing had been a profitable contributor to their marketing mix. This led us to recommend running an incrementality test in their programmatic marketing to validate the modeling results. The incrementality test validated the results we had seen in our media mix modeling. The client was assured that their programmatic campaigns generate awareness and drive down funnel conversions.
Conclusion
Advanced marketing measurement is vital for accurately assessing the performance of different marketing channels. By leveraging tools like MMM, incrementality testing, and data-driven attribution, businesses can gain valuable insights and optimize their marketing strategies effectively. If you want to learn more about marketing measurement, contact Tap In Digital.
We highly recommend ATF for those looking to explore programmatic marketing further. Visit ATF’s website to learn how this powerful channel can enhance your marketing efforts.
Unlock the potential of your marketing strategy with advanced measurement and make informed decisions that drive success.
