Best Practices for Intent Based Segments

ChristinaMorgan

Hi all, posting a question here from one of my customers to bounce it off of the community. They are trying to build out SF reporting to see successes to allow for optimization. Right now, an account can technically qualify for more than one segment so reporting is messy and hard to differentiate which segment has the largest impact. Do any other customers have best practices around this?

• They are leaning towards building a hierarchy for segments (ex: each lower segment would have a filter that it cannot be in any other segment)
• They are curious on how other customers build their Intent-based segments. In the past they listened for a larger timeframe (last 90 days) but wondering if they should change them to shorter ie: Researched more than 3 times in the past 7 days?

Sweety.Rai1

HI Christina,

let me help answering on your question:

on #1 - Your customer's idea of building a hierarchy for segments is a strategic move. This approach can help clarify the impact of each segment by reducing overlap and providing clearer insights into which segments are driving success. Here’s how to implement it:

1. Define Clear Segment Criteria: Start by defining clear, non-overlapping criteria for each segment. This ensures that an account only falls into the most relevant segment, even if they meet the criteria for multiple segments.
2. Implement a Priority System: Assign a priority level to each segment, with the top tier representing the most valuable or engaged accounts. Use this system to assign an account to the highest priority segment it qualifies for.
3. Use Exclusion Filters: When setting up lower-tier segments, include exclusion filters to remove accounts that already belong to a higher-tier segment. This method prevents overlap and simplifies reporting.

on #2 - When it comes to intent-based segmentation, the goal is to capture and act on the most relevant signals of customer intent within an optimal timeframe. The consideration to adjust the listening timeframe from the last 90 days to a more recent window, like the past 7 days, should be informed by the buying cycle and behavior of your target accounts.

• Analyze Buying Cycles: Shorten the listening window if your sales cycle is short or if you’re in a fast-moving industry where interest can peak and wane quickly. This ensures you’re reacting to current interest rather than outdated intent.
• Set Intent Signal Thresholds: Adjusting the criteria to something like "Researched more than 3 times in the past 7 days" could lead to capturing more immediate and possibly more qualified intent but might increase the risk of missing out on accounts that are in the early research phase. Balance is key.
• Segment by Intent Type: Consider segmenting not just by timeframe but also by the type of intent signals (e.g., product-specific research vs. general industry topics). This allows for more tailored messaging and outreach strategies.
• Continuous Testing and Optimization: Regularly review the performance of your segments, especially after making adjustments to the criteria or listening windows. Use A/B testing to refine your approach based on real-world outcomes.

Engage with your customer to iteratively test and learn from these strategies, ensuring that the SF reporting aligns with their goals for optimization and success measurement. Moreover, encouraging community sharing on these practices can unearth new insights and further refine your approach.

hope it helps!

~Sweety

Jana_Marketing_Maven

I think @Sweety.Rai1 has provided a great framework. The only thing I would consider/add is company size versus intent amount. It's honestly something I struggle with as we have a wide variety of target account sizes.

However, if you think about it, this makes a lot of sense. If a company with 20 employees showed 5 intent activities over the past month vs. an organization with 200 employees, the amount of intent showing is higher for the smaller account (intent activities vs. total # of employees).

IOW maybe creating some segments on company size, and then separating those by intent signals - using some of the exclusion/definition options offered above.