BloomGrade helps you understand where to focus your resources before you begin more intensive evaluation. It's a lead analytics tool, not a traditional credit score.

Traditional credit scores generally come into play as part of a formal credit evaluation process and rely on consumer credit bureau data. BloomGrade does not. It uses data already available in your lead flow to generate scores based on historical patterns associated with lead quality, conversion, repayment and other performance measures.

That means you can use BloomGrade across a large volume of incoming leads to understand performance differences across segments and make more informed decisions about where to allocate acquisition, data and evaluation resources.

The value isn't simply the cost of one score compared with another. It's the opportunity to build a more efficient workflow around where you spend your acquisition, data and underwriting resources.

No. BloomGrade adds an earlier layer of analytics to help you understand your lead flow and make more informed decisions about resource allocation.

Think of your evaluation process as a funnel. Instead of putting every incoming lead through the same level of evaluation, BloomGrade provides an earlier signal to support traffic segmentation, routing strategies and workflow prioritization.

Credit bureau data, verification and underwriting remain separate processes, applied according to your organization's established criteria.

This can be especially useful for lenders managing high volumes of top-of-funnel traffic because BloomGrade adds an intelligence layer without requiring third-party credit bureau data at that stage.

Evaluating high volumes of incoming leads can require significant data, time and underwriting resources.

When you're working with a high volume of incoming traffic, applying every available data source and underwriting resource across the entire population can add cost and complexity before you understand how performance varies across your lead flow.

BloomGrade provides an early signal using data already available in the lead flow. That can help you identify performance differences across segments and make more informed decisions about how to allocate downstream resources.

In other words, BloomGrade isn't simply another score to add to your process. It can help you decide where the rest of your process should work hardest.

No. BloomGrade can score leads using data already available in your lead flow, without requiring third-party data.

This makes it possible to introduce an additional analytical signal earlier in your process, before applying more resource-intensive evaluation methods.

BloomGrade is built primarily for top-of-funnel prioritization.

Scores can be returned early in the lead flow to support traffic analysis, segmentation, routing strategies and workflow planning. Your existing underwriting and decisioning processes remain separate and continue to operate according to your organization's established criteria.

How BloomGrade fits into the workflow will depend on your acquisition strategy, current processes and business objectives.

That depends on the problem you're trying to solve.

BloomGrade includes several specialized scores designed to look at different dimensions of lead performance. BloomGrade Core provides a broader view of overall lead performance patterns, while specialized scores offer more focused analytics related to lead quality, conversion, repayment and value.

You don't necessarily need every score. Our team can help you determine which signals are most relevant to your goals and workflow.

Because "Is this a good lead?" can mean different things depending on your objective.

Patterns associated with conversion may differ from those associated with repayment or lead value. A lender interested in early repayment patterns may need a different signal than a lead provider focused on lead valuation or routing.

BloomGrade's specialized scores allow you to focus on the signals most relevant to the problem you're trying to solve.

Yes. BloomGrade scores can be used independently or together.

Some organizations may need one broad signal, while others may combine multiple scores to look at different aspects of their traffic. The right combination depends on your business objectives, workflow and the challenges you're trying to address.

Test it against your own data.

Bloom offers a complimentary data study that allows you to see how BloomGrade scores align with your existing lead population and, where relevant performance information is available, your historical results.

Rather than relying solely on benchmarks or assumptions, you can evaluate how the scores behave on data that reflects your business.

A BloomGrade data study is a complimentary analysis that applies BloomGrade scores to your historical lead data.

We return the scores so your team can examine how different segments of your historical traffic would have been scored and, where relevant performance information is available, compare those signals with historical results.

The goal is to give you a clearer picture of how BloomGrade could fit into your existing process before deciding how you want to use it.

You may not need a massive historical dataset to begin exploring your data.

Larger and more representative datasets generally provide more information for analysis, but organizations with smaller datasets may still be able to conduct a useful study.

Our team can review the data you have available and determine the most appropriate approach based on your dataset and what you're trying to learn.

Not necessarily.

BloomGrade scores can be applied to historical lead data without performance outcomes. However, including relevant performance data can allow for a more meaningful comparison between BloomGrade signals and what actually happened within your portfolio or funnel.

Our team can help determine which data is useful based on what you're trying to learn.

Potentially. A new lending operation may not yet have years of its own historical performance data, but that doesn't necessarily mean it has to wait to begin evaluating additional signals.

BloomGrade models are trained on large-scale lending data rather than requiring each organization to build a model entirely from its own history. As your own data grows, you can continue evaluating how BloomGrade signals align with your population and business objectives.

BloomGrade is designed to return scores in real time and integrate into existing lead workflows.

Implementation timelines depend on your systems, data flow and intended use. Our team can work with your technical stakeholders to determine integration requirements and the appropriate implementation path.