Optimizing Your Database: 10 tips to improve your campaign performance

Maintaining a high-quality database is an ongoing process, and in this article, we will focus on the practical tips to enhance your database's efficiency and boost campaign performance. Addressing common issues such as decreased Open Rates and low message readability, these 10 tips aim to refine your communication strategy and optimize your campaigns.

1. Cyclical Forecasting for Targeted Communication

To ensure your campaigns resonate with the most responsive audience, adopt a cyclical forecasting approach. ?

- Conduct predictions monthly, utilizing 40% of your database for full communication and the remaining 60% for maintenance. This targeted strategy allows you to optimize campaigns and adapt to changing audience preferences.

Use Case: Find profiles who will buy a specific item

2. Dynamic User Movement for Personalized Engagement

This dynamic movement ensures your communication strategy aligns with evolving audience preferences, leading to more personalized and effective engagement.

- Monitor user Open Rates (OR) regularly, and if it falls below 5%, shift users to segments receiving communication, related to high promotions. You can also create a separate segment of customers based on other criteria e.g. number of purchased products in a specific time range (e.g. last 6 months). Add to this segment related to high promotions only those customers who have bought less than 3 products during the last 6 months.

Use Case: Discover average number of transactions per month

3. Discount and Price Personalization for Increased Effectiveness

Leverage forecast data to identify segments with high conversion potential. Adjust promotion sizes based on the segment's propensity, offering tailored discounts. ?

- For loyal customers, provide lower discounts (e.g., 5%), while enticing indecisive customers with higher discounts (e.g., 15%). This personalized approach aims to increase the effectiveness of your offers. Also, you can target heavy buyers who frequently purchase products from specific brands, suggesting higher-priced items from the brands they already know and trust.

Use Case: Find out step discount promotion

Use Case: Suggest heavy buyers higher-priced items from their most frequently purchased brands

4. Reactivation Campaigns to Win Back Inactive Users

Reactivation campaigns can help you win back users who may have become inactive.

- Identify heavy buyers whose buying activity has declined in the current period and reactivate them, sending a series of three re-engagement emails with escalating incentives. Track the percentage of reactivated users after each campaign to estimate the most effective discount levels for individual customer groups. This approach aims to revive interest and win back customers.

Use Case: Find heavy buyers with declining purchase activity

5. Send Messages in the Customer Preferred Communication Channel

Effectively reach specific audiences by connecting through their preferred channels, ensuring more targeted and effective communication.

- Identify user preferences between mobile and desktop channels through aggregates and segmentations.

Use Case: Discover customer preferred channel

6. Test Various Recommendation Types for Enhanced Engagement

Explore different recommendation types available in your database to find the most effective ones for your business. ?

- Implement recommendations at different stages of the customer journey to optimize engagement and drive conversions.

Use Cases: Use and mix different types of recommendations based on our inspiring examples

7. Cost-Effective SMS and Email Campaigns with Propensity Predictions

Maximize campaign effectiveness by targeting customers genuinely interested in specific offers. Lower campaign costs by leveraging propensity predictions, targeting messages only to customers likely to make a purchase. ?

- Utilize the Prediction module to calculate the propensity to buy for customers on specific communication channels, aiming to increase revenue while reducing costs. Create campaigns focusing on customers with the highest propensity to buy from specific brands, optimizing campaign costs and aligning with customer preferences.

Use Case: Reach customers with high propensity to buy

8. Churn Prediction for Proactive Customer Retention

Utilize Churn Prediction to identify customers likely to churn. ?

- Incorporate churn prediction as a parameter in workflow audience segmentation to implement proactive strategies, such as sending emails to customers at high risk of churn, thus enhancing overall business performance.

Use Case: Predict churn

9. Lookalike Predictions for Extended Campaign Reach

Boost conversions by using lookalike predictions to identify customers similar to successful target audiences. ?

- Extend campaign reach by incorporating lookalike audiences into communication strategies, aiming to increase effectiveness by reaching customers with similar qualities to previously successful audiences.

Use Case: Send a campaign to customers who are most likely to buy

10. A/B Testing Control Group for Data-Driven Decisions

Measure campaign effectiveness through A/B testing by incorporating a global control group. ?

- Compare campaign impacts between the main group and the control group to make data-driven decisions, tailoring communication strategies for increased effectiveness.

Use Case: Set up abandoned cart with a control group and A/B tests

The strategies outlined in this guide offer a roadmap for enhancing database quality, ensuring that your campaigns not only reach a wider audience but also resonate deeply with individual preferences. Incorporating these practical tips into your database management process will enhance your campaigns, leading to increased engagement and ROI. As you navigate this journey, remember that it is not just about managing data; it's about creating meaningful connections and delivering value at every touchpoint.

Senior Product Marketing Manager, Ma?gorzata Wojtowicz