Entytle’s Installed Base Segmentation workflow addresses gaps in traditional segmentation such as insights, behavior, and buyer intent

Entytle Inc., provider of the only purpose-built Installed Base Platform (IBP) for Industrial OEMs, introduced the first Installed Base Segmentation workflow, purpose-built for Industrial OEMs.

The Installed Base Segmentation workflow comes at a time when traditional aftermarket & service functions in Industrial OEMs are struggling to keep pace with the continued effects of a pandemic, supply chain disruption, and the evolving economic downturn. This increases the importance of a robust, data-driven, dynamic and actionable customer segmentation to enable scarce resources to be allocated in an optimal way.

Customer or Installed Base segmentation is the first step in defining how to allocate resources, set service levels, and target customers for specific aftermarket, sales, service, or marketing campaigns. Most OEMs today struggle with segmenting their customers deeper than by industry, geography, or revenue. However, these are often not the attributes that determine how a customer wants to interact with an OEM, how resources will be best allocated to grow the business, and what offers will be the best fit for each customer.

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Many OEMs segment their customers into two primary categories based on revenue: Key Accounts (often the top 10-20 customers) and everyone else. The segmentation of key accounts is often done empirically, without a data-driven approach, and does not account for growth potential. The key accounts receive intense focus while others are served in a largely reactive manner. Many OEMs layer in geographic or industry segmentation, and the products a customer has bought from them. This is better than handling every customer the same, however, they still fall short of allocating resources and efforts optimally. Customers with the potential to grow are often not prioritized as their current revenue may not put them into the key account group. If OEMs go deeper in segmenting their customers by products owned, maintenance/service behavior, or wallet share, those are often one-time exercises that quickly become outdated.

OEMs are in this state because it is challenging to implement a data-driven, dynamic and actionable segmentation. There is typically a lack of reliable Installed Base data to power a data-driven segmentation. The data resides in multiple tools, scattered across orgs or functions, duplicated, redundant, and incomplete. This makes it difficult to rely on any insights gained into customer segments due to the compounding effect of narrow account focus (top 10 or 20 customers) coupled with unreliable data.

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This is where Entytle’s Segmentation workflow comes in. The workflow is currently being rolled out to existing customers with implementation configured to each customer’s needs. In one instance, a customer had developed a “behavior-based” customer segmentation model with a consultant that focused on how the end customer interacted with the OEM. The challenge with this model was that it was static and was only re-done every few years in a very manual, time-intensive process. Entytle was able to take their segmentation model and apply it to the OEM’s transaction data and have the segmentation refreshed frequently. The OEM could now ensure appropriate resource allocation and track how their relationship-build efforts with customers were having success. In other scenarios, the OEM may not have a robust segmentation methodology established. In those situations, Entytle leverages its purpose-built Artificial Intelligence models to segment customers based on usage cohorts or wallet share or parts/service entitlement gap. These can be combined with other forms of segmentation (i.e., revenue, geography, industry, products, etc), at a granular level. This enables them to allocate resources, develop account plans and target specific offers to specific customer segments. This is all powered by the single source of truth resulting from using Entytle’s Data Quality Engine that unifies different data sources and cleans, augments, and enriches that data to make it accurate. These approaches can also leverage 3rd party data such as D&B, ZoomInfo, IIR, etc. that can help enhance a segmentation. In all of these situations, what has traditionally taken commercial teams weeks or months, now can be completed in minutes at a fraction of the cost. Also, this also gives OEMs the ability to iterate on different segmentation approaches to find the most relevant and actionable one for their organization and customer base.

Rob Bradenham, Chief Growth Officer at Entytle, had this to say, ”The Segmentation workflow is one of many workflows that we are making available to all of our customers. We are rapidly deploying these across our installed base – taking tasks that have traditionally been long and costly, and making them fast and easy. In the past, OEMs were forced to default to simplistic ways of customer segmentation, reducing the effectiveness of sales & marketing efforts. Our Installed Base Segmentation workflow allows OEMs to move past this tradeoff. This is even more critical in uncertain economic conditions with fewer resources. Our segmentation workflow eliminates the historical tradeoff between data-driven precision and low-cost/fast – OEMs can now have both.”

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