Reports & analytics

Rizer turns every closed-lost deal into structured data. Every recycle reason you assign, every callback date you set, and every won-back deal gets captured and rolled up into reports that help you see patterns you’d otherwise miss.

This article covers the dashboard and all nine reports available in Rizer across the three reporting pillars: Sales execution, Revenue engine optimization, and Pipeline expansion.

The dashboard

The dashboard is your command center. It is divided into the same three pillars as the reports area, so everything you see here has a deeper report behind it.

Sales execution

The Sales execution section of the dashboard covers how well deals are being run, independent of product or market reasons.

KPI cards

At the top of the Sales execution panel you’ll find two summary cards: Win rate (your overall win rate across the selected scope — 35% in the example) and Avg. size (the average deal value — $1,877 in the example). Together they tell you whether you’re winning enough deals and whether the deals you’re winning are the right size.

Execution issues

The Execution issues chart is a horizontal bar chart that summarizes sales process problems identified across your lost deals. Each bar represents the total value attributed to that issue category:

• Qualification — the opportunity wasn’t properly vetted (wrong ICP, no budget, no authority)
• Messaging — the value narrative didn’t land or wasn’t tailored to the buyer
• Cadence — follow-up timing or frequency fell short
• Closing — the close attempt was absent, premature, or poorly structured
• No issue — execution appeared sound; the loss was product, market, or buyer driven
• Data issues — incomplete or inconsistent data made categorization unreliable

This chart separates “we lost because of how we sold” from “we lost because of what we sell.” If Qualification or Cadence dominate, you have coaching and process opportunities. If No issue dominates, the losses are coming from elsewhere.

Owner analysis

Below the issues chart, the Owner analysis section shows each rep’s win rate alongside their top execution issue. In the example shown, Edward Slipszenko sits at 40% with poor qualification as his top issue, Shawn Convery at 28% also flagged for qualification, and Tudor Totolici at 29% with inadequate follow-up. This makes it easy to spot who needs coaching and on what specific area of the sales process.

Win rate trends

At the bottom of the Sales execution panel, the Win rate trends line chart tracks how win rate has moved over time. Use it to spot whether overall performance is improving, declining, or holding steady, and correlate movements against changes you’ve made to process, pricing, or positioning.

Revenue engine optimization

The Revenue engine optimization section focuses on why you’re losing revenue and what’s driving those losses.

KPI cards

The two cards here are Total lost (the total value of closed-lost deals in the selected scope — $456,000 in the example) and Missing features (the portion of that lost value attributed specifically to missing product features — $131,400 in the example). The gap between these two numbers tells you how much of your loss is product-explainable versus something else entirely.

Loss reasons

The Loss reasons donut chart breaks down why deals were lost across two high-level groups. Solution covers loss reasons where your product or offer was the issue — Product, Pricing, and Trust. Buyer covers loss reasons where the buyer’s situation was the issue — Timing & budget, Stakeholders, and Non-responsive.

The relative weight of Solution versus Buyer losses shapes where you should focus. Solution losses call for product and positioning improvements. Buyer losses call for recycling and nurturing strategy.

Top missing features

The Top missing features list connects product gaps directly to revenue impact. Each row shows a feature name, its current roadmap status (Unplanned, Planned, or Implemented), and the total lost value attributed to it. In the example shown, payment integration with multi-currency tops the list at $30,600 lost, followed by email sync at $24,000 and Airbnb integration at $23,400 — all currently unplanned.

When a feature is implemented, the deals that cited it as a loss reason become warm targets for outreach. Rizer can automatically surface those deals for re-engagement when the status changes.

Top competitors

The Top competitors list ranks the competitors you’re losing to most, along with a satisfaction rating and total lost value for each. In the example, Guesty PMS leads at $113,400 lost with a satisfaction score of 1.7 out of 5, followed by Hostaway VRS at $82,800 and Guesty CM at $76,200. Low satisfaction scores next to high lost values suggest deals that switched away reluctantly — those are prime recycling candidates when their contract renewal window approaches.

Pipeline expansion

The Pipeline expansion section tracks the health and output of your recycling activity.

KPI cards

The two cards here are In recycling (total value of deals currently being recycled — $439,200 in the example) and Won-back (total value recovered through recycling after deals were closed as won — $1,200 in the example). The ratio between these two numbers is your recovery rate. A large In recycling figure with a small Won-back figure means either the pipeline is young, timing is off, or follow-through is inconsistent.

Deals in recycling

The Deals in recycling bar chart shows how deal value is distributed across callback timing buckets: No date, > 3 mo, 30d – 3 mo, 14 – 30d, 07 – 14d, 01 – 07d, and Ready (deals past their callback date, ready to re-engage now).

A healthy pipeline has a steady flow moving toward Ready. If No date is large, deals aren’t being properly scheduled. If Ready is large and growing, follow-up isn’t happening consistently after deals become due.

Won-back (after recycling)

The Won-back chart shows recovered deal value by month, giving you a month-by-month view of what recycling is actually producing. Spikes often correlate with workflow activity, seasonal patterns, or periods when a large number of callbacks came due simultaneously. In the example shown, February sees a spike in won-back value with no activity in March or April yet.

Nurturing

If nurturing is enabled, the Nurturing widget shows your active and draft workflows along with their enrollment and engagement performance. Each row shows the workflow name, its status (Active, Paused, or Draft), the number of companies currently enrolled, and open and click rates. In the example shown, Price Objection – ICP Tier 1 is paused with 80 companies enrolled, Feature Gap – Switched is paused with 55 companies, and several workflows — including Price Objection – ICP Tier 3, Timing Block – Stayed, and Power Problem – Lead — are in draft with over 90 companies each waiting to be activated.

Reports

To go deeper than the dashboard, open the reports area from the main navigation. Reports are organized into the same three pillars — Sales execution, Revenue engine optimization, and Pipeline expansion — with each pillar containing three reports.

Every report shares the same filter bar at the top. You can switch between Deals and Value, filter by owner, segment, product, and decision maker, set a time range, and toggle between Monthly and other groupings. The axis and percentage total toggles let you flip how the chart is oriented or normalize bars to 100% for easier comparison. These filters apply to both the chart and the breakdown table below it, so you can slice the same data multiple ways without leaving the report — moving from a team-wide view down to a single rep, a specific product, or a particular time window.

Sales execution reports

Sales execution reports answer the question: how well are we running deals, and where is process costing us wins?

Issues

The Issues report shows lost deal value broken down by execution issue category and owner. The stacked bar chart gives you a side-by-side view of each rep’s total lost value, with each segment representing one issue category. The breakdown table below the chart quantifies each combination so you can see exactly how much value each rep has attributed to each issue.

In the example shown, Messaging is the largest issue category overall at $175,200, with Shawn Convery ($64,200) and Edward Slipszenko ($62,400) accounting for most of it. Qualification follows at $127,800 and Cadence at $106,200. These aren’t performance rankings — territory size, deal volume, and product mix all affect the numbers — but the relative weight of categories per rep points directly to where coaching conversations should start.

Use the owner filter to isolate a single rep and look at their pattern in detail. Use the segment or product filter to check whether issues are concentrated in a particular part of the business rather than spread evenly across the team.

Trends

The Trends report shows the same issue categories plotted month by month, so you can see whether specific problems are improving, worsening, or staying flat over time. The stacked bar chart gives you a month-by-month view of lost deal value by issue category, and the breakdown table shows the exact figures for each category per month.

In the example shown, Messaging has been consistently the largest issue category throughout the year, with peaks in June ($21,000) and July ($22,200). Cadence spiked in May ($14,400) and dropped to $0 in September before recovering. These movements are meaningful when correlated with changes you made to process or team structure during that period.

This is your validation tool. If you adjusted qualification criteria, changed the follow-up cadence, or ran a coaching initiative, the Trends report is where you confirm whether it moved the needle. Switch the time range to zoom in on a specific quarter, or switch to quarterly grouping for a broader view of direction.

Reasons

The Reasons report shifts the lens from execution issues to loss reasons — the actual reasons deals were marked as closed-lost. The chart breaks lost value down by the six loss categories across Solution (Product, Pricing, Trust) and Buyer (Timing & budget, Stakeholders, Non-responsive), shown per owner.

In the example shown, Pricing dominates at $162,000 total lost value, with Shawn Convery ($64,800) and Edward Slipszenko ($56,400) leading. Product losses sit at $70,200 and Timing & budget at $63,000.

This is where you separate “we lost because of how we sold” from “we lost because of what we’re offering or who we’re targeting.” If Pricing losses are high across the board, the problem is likely positioning, packaging, or competitive dynamics — not individual rep behavior. If one rep has disproportionately high Product or Trust losses, that’s worth digging into at the deal level. Click any bar segment or table cell to drill down to the underlying deals that make up that number.

Win-loss

The Win-loss report tracks lost deal volume and value per owner over time. The stacked bar chart shows monthly lost deal value for each rep, and the breakdown table gives you the exact figures month by month. You can switch the primary dimension between Lost and Won to compare both sides of the picture.

In the example shown, Shawn Convery leads in total lost value over the period at $152,400, followed by Edward Slipszenko at $129,000 and Tudor Totolici at $108,600. Month-by-month movements tell a more nuanced story — Shawn’s losses spike in July ($22,200) and again in October and January, which may reflect deal timing, territory activity, or pipeline composition at those points.

Use this report to understand volume and distribution across the team over time, not just point-in-time snapshots. Pair it with the Issues and Reasons reports to connect how much each rep is losing with why they’re losing it.

Revenue engine optimization reports

Revenue engine optimization reports answer the question: why are we losing revenue, and what patterns are hiding inside that loss?

Lost drivers

The Lost drivers report shows lost deal value broken down by loss category and competitor. The stacked bar chart gives you a competitor-by-competitor view of total lost value, with each segment representing one of the six loss categories. The breakdown table below quantifies each combination so you can see exactly how much value was lost to each competitor for each reason.

In the example shown, Guesty is the largest competitor bar at around $140,000 in total lost value, with Pricing ($46,200) and Product ($21,000) as the leading categories. Hostaway follows closely at just over $100,000, also dominated by Pricing ($46,200). In-house solutions account for around $93,000, with Pricing ($24,000) and Timing & budget ($24,600) nearly tied. Unknown solution appearing as a significant bar is a data quality signal — those are deals where reps didn’t record a competitor, making the loss harder to act on.

Use this report to build competitive context. If Pricing losses cluster heavily against Guesty and Hostaway, you have a specific matchup problem, not a general pricing problem. Filter by product to check whether the competitive dynamic shifts depending on which product was in play, or filter by owner to see whether certain reps are more exposed to specific competitors than others.

Trends

The Trends report plots loss categories month by month so you can see how the reasons you’re losing deals are shifting over time. The stacked bar chart shows monthly lost deal value for each category, and the breakdown table gives you the exact figures per category per month.

In the example shown, Pricing is consistently the largest loss category across the year, ranging from $8,400 in May to peaks of $18,600 and $20,400 in June and September. Product losses grow noticeably toward the end of the year, reaching $12,000 in December — which may point to increasing feature gap pressure as the competitive landscape shifts. Non-responsive losses spike in January at $10,800 after being relatively stable throughout the year.

This is the report to return to after making a change. If you updated pricing packaging, ran a competitive enablement initiative, or adjusted how reps handle timing objections, the Trends report is where you confirm whether loss patterns actually shifted. Switch to quarterly grouping for a higher-level view of direction, or zoom into a specific six-month window to isolate the period you care about.

Insights

The Insights report is different from the other reports in this section. Instead of a chart and breakdown table, it presents AI-generated observations drawn from patterns across your recycled deals, paired with a specific recommendation for each one. Each row shows a category, the pattern Rizer identified, and a concrete next step.

In the example shown, insights cover several categories:

• Competitors — Guesty is linked to 44 recycled deals across both products, with “Undercut by competitor” and “Unclear value” as the top co-occurring reasons. Recommendation: create a Guesty-specific response playbook auto-inserted into relevant workflows.
• Pricing — “Too expensive” appeared on 18 recycled deals among English-speaking Tier 1 targets, frequently alongside “Undercut by competitor.” Recommendation: activate the Price Objection workflow with ROI-framing templates against Hostaway and Guesty.
• Timing & budget — 36 recycled deals have timing or budget blockers, with callbacks clustered 120–150 days out. Recommendation: turn on the Timing Block and Budget Wall workflows with matching callback estimates.
• Product missing features — “Missing feature” drove 29 recycled deals for Reservation System, clustered around email sync and multi-currency payments. Recommendation: activate Feature Gap workflows and auto-move those deals to Ready to callback when the relevant features is implemented.

Treat each insight as a hypothesis grounded in your data, not a directive. The recommendation tells you what Rizer thinks is the highest-leverage action — but you decide whether the context supports it. Use the Category filter at the top to focus on a specific area, and follow the View links within insights to jump directly to the underlying deals or feature requests they reference.

Pipeline expansion reports

Pipeline expansion reports answer the question: how is recycling performing and what is it actually producing?

Callback

The Callback report shows how deal value is distributed across callback timing buckets, broken down by loss category. The stacked bar chart gives you a view of the full recycling pipeline from No date through to Ready, with each segment representing one of the six loss categories. The breakdown table below shows the exact value per loss category per timing bucket.

In the example shown, the 30d – 3 mo bucket holds the largest concentration of value at just over $200,000, with Pricing ($78,000) and Product ($31,200) as the dominant categories. The 3 – 6 mo bucket holds around $93,000, also led by Pricing ($31,200). The No date and > 6 mo buckets are nearly empty — a healthy sign that deals are being scheduled rather than left in limbo. The Ready bucket shows very little value, which either means deals are being picked up promptly when they come due, or the pipeline hasn’t matured enough yet to generate a steady flow.

Use this report to manage pipeline health and workload. A few warning signs to watch for:

• A large Ready bucket that keeps growing is a follow-up backlog problem
• A large No date bucket means deals are being recycled without a plan
• Everything piling up in the same timing window creates workload spikes — adjust callback scheduling rules to spread the load

Filter by loss category to see whether specific reasons tend to be scheduled further out. Timing & budget losses, for example, often warrant longer callback windows than Pricing losses where the competitive window may be tighter.

Wins

The Wins report shows deals that were closed as won after going through recycling, plotted by month and broken down by the original loss category. This is your direct measure of recycling output — not deals in the pipeline, but deals actually recovered.

In the example shown, the report is filtered to a specific owner (Shawn Convery), product (Channel Manager), and recycling reason (Switched). The only won-back value so far is $1,200 in February 2026, attributed to a Pricing loss category, with nothing yet in March. This is a young dataset — the pipeline visible in the Callback report hasn’t had time to produce wins at scale yet, which is normal in the early stages of a recycling programme.

As the dataset grows, patterns emerge. Timing & budget wins often cluster in periods that follow callback spikes. Pricing wins tend to correlate with specific workflow activations or competitive moments. Filter by owner to compare recovery rates across the team, or filter by product to see whether certain offerings are more recoverable than others once a deal has been recycled.