Analyzr
G2M Insights · Marketing
Analyzr is a no-code machine learning platform for B2B sales and marketing teams. It builds predictive models from customer data and now runs as the G2M Platform.
About Analyzr
What Is Analyzr
Analyzr is a predictive analytics service built for B2B sales and marketing teams that want model output without hiring a data science staff. You connect customer and campaign data, pick a business question, and the platform returns scores, segments, and spend guidance you can act on. The work happens in a browser and through an API rather than in a notebook.
G2M Insights, a Denver-based analytics firm, launched Analyzr in June 2022 as packaged machine learning behind an API. Customers plugged the output into production systems and used it to rank prospects, group accounts, and judge which channels earned their budget. That core idea still holds.
The name changed in May 2024. Analyzr became the G2M Platform, and analyzr.ai now redirects to g2m.ai. New accounts start at app.g2m.ai. If you search for Analyzr reviews or old documentation, expect two names for one product. The limits are worth knowing up front. Pricing comes from a sales conversation, not a checkout page. The models are only as good as the CRM and marketing data you feed them, and a messy pipeline produces confident nonsense.
Getting Started
- Request a trial or a demo at g2m.ai. The team sets up a workspace and walks through the use cases that fit your data.
- Connect your sources. Typical inputs are CRM records, marketing automation history, finance data, and third-party firmographics.
- Choose a question. Propensity scoring, customer segmentation, or marketing mix modeling are the common starting points.
- Review the model output with your team. Check the scored accounts against what sales already believes, and flag anything that looks wrong before it reaches a workflow.
- Ship the results. Scores land in dashboards or return through the API into your CRM, ad platform, or reporting stack.
Product Information
A quick look at Analyzr's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- B2B marketing leaders
- Sales operations analysts
- Revenue teams at mid-market and enterprise companies
Tasks
- Scoring inbound and target accounts
- Grouping customers into segments
- Measuring channel contribution
- Finding churn and profitability patterns
Scenarios
- Quarterly pipeline planning
- Deciding next quarter's campaign budget
- Adding analytics without new headcount
Key features
No-Code Model Building
The platform wraps model training in a guided interface. You select a business question, map your fields, and the system handles feature preparation and model selection. Output arrives as scores and charts you can read without a statistics background. For a team that has data but no modeling staff, that removes the largest blocker.
Propensity Scoring
Propensity scoring ranks accounts or contacts by how likely they are to take a desired action, such as buying, expanding, or renewing. Sales gets a priority order instead of a flat list. The value depends on closing the loop: scores need to reach the CRM and the reps need a reason to trust them, which usually means reviewing early results together.
Customer Segmentation and Clustering
Clustering groups customers by shared behavior rather than by industry label or company size. That surfaces segments you might not have named, such as accounts that buy fast and expand slowly. Marketing can then write for a real pattern and sales can adjust territory or outreach plans around it.
Marketing Mix Modeling and Attribution
Marketing mix modeling estimates how much each channel contributes to revenue, including channels that are hard to track at the click level. The platform pairs that with spend recommendations, so the output answers a budget question rather than just reporting history. Finance teams tend to care about this more than the model mechanics.
Continuous Monitoring and Root-Cause Analysis
The G2M Platform monitors key metrics and flags shifts as they happen, with automated analysis of what moved the number. Instead of waiting for a monthly report, a revenue leader can see a pipeline drop and a likely cause in the same view. The feature is only as useful as the metric definitions you set up at the start.
API and Single-Tenant Deployment
Predictions return through an API that plugs into production systems, so scores can drive routing, targeting, and reporting without manual exports. G2M also describes single-tenant deployment, which matters to buyers in regulated industries who need their data separated from other customers. Confirm the current contract terms during the trial, since deployment details sit behind the sales process.
Pros and cons
Pros
- The interface assumes no coding, so revenue teams can run predictive analytics without a data scientist in the loop.
- Scores and segments return through an API, which makes them usable inside existing CRM and ad workflows.
- The platform covers the full path from data prep to monitoring, so you aren't assembling four separate tools.
- Marketing mix modeling and propensity scoring answer budget and prioritization questions that show up in every quarterly review.
- The advisory side of G2M Insights means the model work comes with people who can interpret the output with your team.
Cons
- There is no public price list. You need a sales conversation before you know whether the platform fits your budget.
- Weak or fragmented CRM data will produce unreliable scores, and cleaning it is your job, not the platform's.
- The product carries two names. Documentation, blog posts, and login links are split between Analyzr and G2M, which slows down research.
- Small teams with short sales histories may not have enough data for a useful model, and there is no cheap self-serve tier to test that limit.
Frequently asked questions
Analyzr is used for predictive analytics in B2B sales and marketing. Teams connect customer data and get propensity scores, customer segments, and channel contribution estimates that guide targeting, budgeting, and account planning.
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