MarTech Conference Discusses Engineering Consent For Better Marketing
Marketing teams face challenges in turning opt-ins into valuable data assets, but cross-functional alignment can help bridge the gap. Compliance pressure and privacy controls can power better personalization.
Original reporting · martech.org
Original: “Beyond the opt-in: Engineering consent for better marketing”
Read “Beyond the opt-in: Engineering consent for better marketing” at MarTech →
How this was written. GMS Agency Desk wrote this article with a language model from MarTech’s reporting (model: @cf/meta/llama-3.3-70b-instruct-fp8-fast); it describes that reporting rather than adding to it. The original, linked above, is the full story.
Key points from MarTech’s report
- Cross-functional alignment is key to bridging the gap between capturing opt-ins and earning engagement.
- Transparency and clarity are crucial when collecting data and requesting permissions.
- Context is essential for governing execution and handling the disconnect between buyer preferences and behavioral signals.
- Data integrity is critical for high-performing AI, and teams must ensure that they have high-quality data tied to verifiable consent.
- Operational silos and misalignment between teams can hinder the effectiveness of a modern preference center.
The MarTech Conference recently explored how to move beyond initial opt-ins and build trust with customers, according to MarTech. This is crucial as the gap between capturing an email and earning real engagement is where many growth strategies stall.
A key challenge for marketing teams is navigating the daily friction between capturing opt-ins and earning engagement. Many teams rely on standard preference centers, while others operate out of compliance fear, highlighting the need for a better approach.
Industry practitioners discussed how to optimize for the value of the relationship after a customer says yes, rather than just focusing on the number of people who opt-in. This requires a clear understanding of the value exchange when collecting data and being transparent about how it will be used.
Requesting permissions at the right moment can also help increase high-value channel opt-ins. For example, asking for delivery alerts at the point of purchase can make the request feel more natural and reciprocal, leading to a higher opt-in rate.
Another hurdle for operational leaders is handling the disconnect between buyer preferences and behavioral signals. This requires understanding the distinction between consent and preferences, and using context to govern execution.
A modern preference center should be able to propagate user choices across different systems, including customer data platforms and outbound engines. However, this can be challenging due to operational silos and misalignment between different teams.
The use of artificial intelligence raises the stakes for data integrity, and teams must ensure that they have high-quality data tied to verifiable consent. This requires clear mechanics for handling preference revocations and maintaining data lineage.
Questions and answers
What is the main challenge for marketing teams in turning opt-ins into valuable data assets?
The main challenge is navigating the daily friction between capturing opt-ins and earning engagement, and building trust with customers.
How can teams increase high-value channel opt-ins?
Teams can increase high-value channel opt-ins by requesting permissions at the right moment, such as asking for delivery alerts at the point of purchase.
Why is data integrity important for AI?
Data integrity is critical for high-performing AI, as it requires high-quality data tied to verifiable consent to produce accurate results.
