By its very nature, personalization can be more difficult to track than sales, but some metrics can at least give you a sense of where you’re headed. Here are some metrics a B2B manufacturing company might track:

• Repeat visitors: Analyze the frequency and patterns of visitors returning to your site. Look into what specific personalized elements or content might be encouraging patterns. For instance, track if certain personalized recommendations lead to higher revisit rates.

• Number of visitors from a particular company: Dive deeper into the traffic coming from specific companies. Understand each group’s engagement patterns and which content aligns with their business needs.

• Customer acquisition cost: Assess the cost-effectiveness of personalized campaigns compared to broader marketing strategies. Calculate the expenses incurred per customer acquired under each approach to refine your budget allocation.

• Dwell time: Examine how long users spend on specific personalized pages to identify correlations between longer dwell times, different personalization strategies, and conversion rates.

• Which assets appeal to prospects (with demographics): Analyze demographic data to determine which personalized assets resonate with different audience segments. Understand if certain demographics prefer specific types of personalized marketing or recommendations over others.

• User relevance: Track click-through rates or time spent on personalized content to assess how well variants match the users’ needs and interests.

• Engagement rates: Page views, dwell time, social shares, or interactions with personalized elements could inform your future strategy.

• Customer, supplier, and vendor feedback: Gather feedback regarding personalized product descriptions or service customizations to refine offerings and communication with business partners.

• Impact on order volume: Measure the difference in orders between clients engaging with personalized offerings and those who don’t, indicating the value derived from customization efforts.

• Preference change rates: Track how effectively personalization efforts influence user responses. If browsing behavior shifts after exposure to an individualized product recommendation, it indicates successful personalization influencing their preferences.

• Content longevity: Measuring the decay rate of personalized recommendations' effectiveness over time or the frequency of content updates needed to maintain relevance helps assess content longevity.

• Trust and transparency index: This can involve surveys, feedback, or sentiment analyses to gauge users' trust levels in recommendations or personalized content provided by the DXP. Factors such as clear explanations for transparent data usage and privacy policies contribute to this index.

A composable platform like Magnolia can bridge the gap between your customer support, marketing, and data departments. With everyone having access to the same data dashboards and templates, developing small-scale tasks aligning with big-picture strategies is no longer a mammoth task.

How to translate your test results into a personalized experience that boosts conversions

For your data analysis to inform successful organizational decisions, you need to make continuous testing part of your routine. First, you should consider your A/B test design to ensure that the setup aligns with your business objectives. Outline what you aim to learn before running the actual test and identify key performance indicators for each variant. For instance, if the goal is to re-engage existing customers on your email list, track the conversion rate for links sent within that customer segment.

By formulating a hypothesis that directly ties to your business goals you can ensure test results actually lead to actionable strategies. You should also consider your sample size to guarantee that you analyze statistically relevant data. If you’re uncertain, study recommended practices within your niche instead of generic best practices.

Finally, don’t forget that A/B testing is an iterative process. Every time you’ve run a test, those insights should inform the next one as well as future marketing campaigns. This requires you to document your decision-making process, user feedback, and tests to look back at the details if necessary.

To follow a data-based personalization strategy, you want to set up rules for monitoring, analysis, and resulting adjustments within your DXP. That way, you don’t need to wait for the next annual report to see results. Instead, you can consistently adjust your check-ins to your goals, whether that’s a seasonal campaign or a quarterly alignment meeting.