SEGMENT CONVERSION ANALYSIS
Determine Which Segmentation System Clusters
Represent Your Best Converting Customers
with a Segment Conversion Analysis
What Sets Us Apart
A Segment Conversion Analysis Report is the output of a segmentation analysis performed by Inbound Insight that allows you to determine which demographically determined customer segments are most and least likely to convert based on any consumer segmentation system.
We help you to understand your customers’ conversion rates based on Connex, Niches, Personicx, Energy Consumer Dynamics or even any Propensity Model, quickly and at a modest price. Most other marketing data solution providers only offer “canned” reports based on core demographics (e.g., the Customer Portrait Report) and nothing more. We believe you should be able to analyze customers using the segmentation system (or propensity model) of your choice.
The other factor that sets us apart with respect to our Customer Segmentation Analysis is that we provide you with the cluster system data that has been appended to the name and address records you provide for the report. Typically, when you run a demographic portrait report all you get is the report itself…no data. Getting the data back allows you to refine the analysis by incorporating your own specific knowledge of the customer (e.g., what product did they purchase, how many times have they purchased, total lifetime value). You can also use the appended cluster data as an input into your own analytic/data science models.
As a follow on project, our clients often enhance additional customer records beyond those provided with the Segment Conversion Analysis.
Segment Conversion Analysis – Key Benefits
You get the following key benefits from a Segment Conversion Analysis:
- Detailed understanding of which groups of prospects convert best (and worst)
- Ability to prioritize which segments to focus on for conversion and follow on prospecting campaigns
- Use the 80/20 rule to determine which segments should not be contacted via expensive media
- Knowledge of which segments convert the best — and the worst — can help you prioritize your prospect and customer outreach efforts. For example, using the 80/20 rule, you may decide NOT to send postcard mailers to the bottom 2 or 3 converting deciles.
- Use the knowledge of how your customers differ from the typical customer in your market area to establish best target audience characteristics for acquisition programs
- Segments are defined by demographics and include deep qualitative information that can help refine messaging.
Segment Conversion Analysis – Background
Here are some of segmentation systems that can be used for the Customer Conversion Analysis:
- Connex – 130 granular Household Clusters, 16 Family Clusters and 35 Digital Clusters
- Niches – 26 primary “niche” clusters and 108 “super-niche” clusters
- Personicx – 70 clusters with optional groupings
- Energy Consumer Dynamics – 13 energy-focused clusters
Note that any Propensity Model (typically with 10, 20 or 100 segments) can also be used for Customer Conversion Report.
There are a few ways to perform this analysis:
- Customer Sample vs. Population: compare existing customers to segment profile of the market area served — this is not really a conversion analysis and is more of a market penetration analysis similar to a Customer Profile Report.
- Customer Sample vs. Prospect Sample: compare a random sample of customers vs. a random sample of prospects – while this data is typically easier to pull and has the advantage of a relatively large customer sample, the results will not be as accurate as the next method. Typically we seek to analyze a minimum 5K to 10K each of prospects and customers.
- Prospects Converting to Customers: compare individuals who become customers from within a group of prospects – more accurate since this is a “longitudinal” study but typically need a large prospect sample in order to get enough customers to analyze with statistical validity. For example, at a conversion rate of 10%, and a bare minimum 3,000 customer records to analyze, the prospect would need to be about 30,000 records.
Here is an example of an Index Analysis using Energy Consumer Dynamics.
Visualizing Your Data with a Segment Conversion Report
Segment Conversion Reports can be analyzed by segment or by grouping multiple segments into “deciles” which each represent about 10% of the sample. The latter is typically done when there are more than a few dozen clusters.
Below at the left is a table showing the 13 Connex Household Clusters that make up the top-converting decile. To the right is the associated bar chart showing the index of each of the ten deciles with the index of 155 indicated for the first decile.
Segment Conversion Analysis Report – Use Cases
Here are some key use cases for customer segment analyses:
- Understanding customer profile based on a wide variety of demographic elements and/or Personicx
- Creating groupings of clusters for common messaging
- Prioritizing which segments to reach out to
- Creating look alike target audiences for lists and digital outreach
- Comparing existing customer segment profiles (e.g., customers vs. prospects, customers of Product A vs. Product B, customers in Region A vs. Region B).
Segment Conversion Report – Case Study
One of our clients wanted to know which Connex clusters comprised the majority of its customers so it could focus on reaching out to a look-alike audience and to know what were the differences in Connex profiles between customers and prospects to determine if some clusters were converting at a higher rate than others.
By appending the 130 Connex clusters to 10,000 prospects and 10,000 customers we were able to determine which clusters were most common within their prospect and customer samples. By creating an index and comparing customers to prospects we were able to infer which segments converted better.
Knowing which clusters to avoid allowed the client to choose not to send out mailers to abandoned cart or email opt-in prospects.
This client sends automated mail to hand-raiser prospects who provide an email address on a daily basis. Now they append Connex to each name and address in order to avoid mailing to low priority prospects, improving their direct mail ROI.