
AI Listing Performance Monitor
Get listing performance digest - just enter listing urls, portal stats, market data.
Listing Performance Monitor
Generate a data-driven listing performance digest. Provide the listing URLs on major portals, current view/save counts, days on market, asking price, square footage, and local market data. Receive a complete analysis including portal-by-portal metrics vs. area benchmarks, price positioning against comps, absorption context, conversion funnel performance, creative asset indicators, and a prioritized recommended actions matrix with specific price-reduction triggers and remarketing tactics., -
Listing Identification
Primary Listing Address: [[Full Property Address]], [[City]], [[State]] [[ZIP Code]]
Property Type: [[Single Family / Condo / Townhouse / Multi-Family]]
Bedrooms / Bathrooms: [[Number of Bedrooms]] bed / [[Number of Bathrooms]] bath
Living Area: [[Square Footage]] sq ft
Asking Price: $[[Asking Price]]
List Date: [[Original List Date]]
Days on Market (as of report date): [[Current Days on Market]]
Listing Agent / Brokerage: [[Listing Agent Name]], [[Brokerage Name]]
Portal URLs Provided:
- Zillow: [[Zillow Listing URL]]
- Realtor.com: [[Realtor.com Listing URL]]
- MLS / Broker Reciprocity: [[MLS Number or Portal URL]]
Report Date: [[Report Date]]
Data Pull Date: [[Data Snapshot Date]]
Market Reference Area: [[City / County / Zip or Neighborhood Name]], -
1. Per-Portal Metrics, Views, Saves, and Days-on-Market Benchmarks
Metrics are pulled from each portal's public and agent-facing dashboards where available. Views count unique listing page loads. Saves (favorites) indicate buyer interest strength. Compare current DOM against the area median for similar properties.
Zillow Performance
- Views (lifetime): [[Zillow Total Views]]
- Views (last 7 days): [[Zillow 7-Day Views]]
- Views (last 30 days): [[Zillow 30-Day Views]]
- Saves / Favorites: [[Zillow Total Saves]]
- Saves rate vs. views: [[Zillow Save Rate Percent]]%
- Days on Market: [[Current Days on Market]]
- Area median DOM (3+ bed, similar price band): [[Area Median DOM]] days
- Performance vs median: [[Above / Below / At]] median by [[DOM Difference]] days
Realtor.com Performance
- Views (lifetime): [[Realtor.com Total Views]]
- Views (last 7 days): [[Realtor.com 7-Day Views]]
- Views (last 30 days): [[Realtor.com 30-Day Views]]
- Saves: [[Realtor.com Total Saves]]
- Saves rate vs. views: [[Realtor.com Save Rate Percent]]%
- Days on Market: [[Current Days on Market]]
- Area median DOM: [[Area Median DOM]] days
MLS / Syndicated Portal Performance
- Views (where tracked via ShowingTime or MLS stats): [[MLS Tracked Views]]
- Showing requests / appointments booked: [[MLS Showings Booked]]
- Agent feedback notes logged: [[Number of Feedback Entries]]
- Primary feedback themes: [[Summarized Feedback Themes e.g. "price high, needs paint, great location"]]
Portal Comparison Summary Table
| Portal | Total Views | 7d Views | Saves | Save Rate | DOM vs Median |
|---|---|---|---|---|---|
| , , | , , , - | , , , | , , - | , , , - | , , , , - |
| Zillow | [[Zillow Total Views]] | [[Zillow 7d]] | [[Z Saves]] | [[Z %]]% | [[+/- X days]] |
| Realtor.com | [[R Total Views]] | [[R 7d]] | [[R Saves]] | [[R %]]% | [[+/- X days]] |
| MLS / Other | [[M Views]] | [[M 7d]] | [[M Saves]] | [[M %]]% | [[+/- X days]] |
Interpretation: [[Brief narrative on which portal is driving the most engagement and whether DOM is competitive.]], -
2. Price-to-Market and Price-per-Square-Foot Comps
Current list price is evaluated against recent closed sales of similar homes. Adjustments made for GLA, condition, updates, location, and lot features. Price per square foot is a key quick benchmark.
Asking Price vs. Indicated Market Value Range
- List price: $[[Asking Price]]
- Estimated market value range (reconciled from comps): $[[Low Value]], $[[High Value]]
- Price-to-market ratio: [[Price to Market Ratio]]% (list price as % of indicated value)
- Over / under market: [[Over / Under / Aligned]] by $[[Dollar Difference]]
Comparable Sales Table (Closed within last 6 months, similar 3+ bed properties within [[Radius]] miles)
| Address | Sale Date | Sale Price | GLA (sq ft) | Beds/Baths | $/Sq Ft | DOM | Notes |
|---|---|---|---|---|---|---|---|
| , , - | , , , - | , , , | , , , - | , , , | , , - | , - | , , - |
| [[Comp 1 Address]] | [[Comp 1 Date]] | $[[Comp 1 Price]] | [[Comp 1 GLA]] | [[Comp 1 Beds]]/[[Comp 1 Baths]] | $[[Comp 1 PSF]] | [[Comp 1 DOM]] | [[Comp 1 Notes e.g. updated kitchen]] |
| [[Comp 2 Address]] | [[Comp 2 Date]] | $[[Comp 2 Price]] | [[Comp 2 GLA]] | [[Comp 2 Beds]]/[[Comp 2 Baths]] | $[[Comp 2 PSF]] | [[Comp 2 DOM]] | [[Comp 2 Notes]] |
| [[Comp 3 Address]] | [[Comp 3 Date]] | $[[Comp 3 Price]] | [[Comp 3 GLA]] | [[Comp 3 Beds]]/[[Comp 3 Baths]] | $[[Comp 3 PSF]] | [[Comp 3 DOM]] | [[Comp 3 Notes]] |
| [[Comp 4 Address]] | [[Comp 4 Date]] | $[[Comp 4 Price]] | [[Comp 4 GLA]] | [[Comp 4 Beds]]/[[Comp 4 Baths]] | $[[Comp 4 PSF]] | [[Comp 4 DOM]] | [[Comp 4 Notes]] |
| [[Comp 5 Address]] | [[Comp 5 Date]] | $[[Comp 5 Price]] | [[Comp 5 GLA]] | [[Comp 5 Beds]]/[[Comp 5 Baths]] | $[[Comp 5 PSF]] | [[Comp 5 DOM]] | [[Comp 5 Notes]] |
Price per Sq Ft Analysis
- Subject list price per sq ft: $[[Subject PSF]]
- Median closed comp $/sq ft (adjusted): $[[Median Comp PSF]]
- Subject vs median: [[Above / Below]] by $[[PSF Difference]] / sq ft ([[Percent Diff]]%)
Recommended List Price Range for Quick Sale: $[[Suggested Low]], $[[Suggested High]], -
3. Absorption Rate and Months-of-Inventory Context
Absorption rate measures how quickly homes are selling in the submarket. Months of inventory indicates supply relative to demand.
Local Market Snapshot (as of [[Data Month]])
- Active listings (similar property class): [[Active Listings Count]]
- Closed sales last 30 days (same segment): [[Closed Sales 30d]]
- Absorption rate: [[Absorption Rate]]% (homes sold per month as % of active)
- Months of inventory: [[Months of Inventory]] months
- Market pace classification: [[Seller's / Balanced / Buyer's]] market
Subject Implications
- At current pace, a well-priced, well-presented home in this segment typically sells in [[Typical DOM Target]] days.
- Current DOM for subject ([[Current Days on Market]]) places it in the [[Top / Middle / Bottom]] [[Percentile]] of recent sales velocity.
- If absorption continues at [[Absorption Rate]]%, expect [[Projected Sales in Next 30 Days]] additional sales in the segment.
Market Velocity Notes: [[Narrative on inventory trend, new listings entering market, interest rate or seasonal effects.]], -
4. Conversion Funnel, Views to Showings to Offers
Track movement through the buyer decision stages with industry benchmark ranges for mid-tier suburban/urban residential listings.
Sample Funnel Performance (Current Listing)
| Stage | Count | % of Prior Stage | Benchmark Range | Subject vs Benchmark |
|---|---|---|---|---|
| , , - | , , - | , , , , , | , , , , - | , , , , , , |
| Portal Views (combined) | [[Total Unique Views]] | , | , | , |
| Saves / Favorites | [[Total Saves]] | [[Save %]]% | 6, 15% | [[On / Above / Below]] |
| Inquiry / Contact | [[Inquiries]] | [[Inquiry %]]% | 8, 20% | [[On / Above / Below]] |
| Showings Booked | [[Showings]] | [[Showing %]]% | 15, 30% | [[On / Above / Below]] |
| Offers Received | [[Offers]] | [[Offer %]]% | 5, 15% | [[On / Above / Below]] |
Funnel Health Diagnosis: [[Summary e.g. "Strong initial views and saves, but showing conversion below benchmark indicating possible pricing or photo issues."]]
Benchmark Sources (typical U.S. residential 2025, 2026 data): Views-to-saves 8, 12% average for active listings; showing-to-offer conversion often 8, 12% when priced at market., -
5. Photo and Description Performance Indicators
Creative quality heavily influences click-through and time spent on listing.
Photo Performance
- Number of photos uploaded: [[Photo Count]]
- Click-through rate from search results to detail page (where measured): [[CTR Percent]]%
- Average time on listing page: [[Time on Page Seconds]] seconds
- Area median time on page: [[Median Time]] seconds
- Heatmap / most viewed photos: [[Photo Numbers or Descriptions e.g. "kitchen, primary bath, exterior front"]]
Description Performance
- Description word count: [[Word Count]]
- Key search terms included: [[Keywords e.g. "updated, granite, fenced yard, move-in ready"]]
- Readability / engagement signals: [[e.g. "Multiple paragraphs, bullet features, call to action for showings"]]
- Estimated impact: [[Positive / Neutral / Needs Rewrite]]
Recommendations on Creative
- Minimum photo count for competitive listings: 25, 35 high-quality images.
- Professional twilight or drone shots improve exterior engagement.
- Descriptions should front-load unique selling points in first 2, 3 sentences., -
6. Recommended Actions Matrix
Prioritized actions based on current metrics. Triggers are guidelines; market conditions and property specifics may warrant earlier or later action.
Action Triggers and Tactics
| Trigger Condition | Recommended Action | Expected Impact | Priority | Timing |
|---|---|---|---|---|
| , , , , , - | , , , , , | , , , , - | , , , | , , |
| 7-day views < [[Low Views Threshold]] after first 14 days live | Price reduction of 2.5, 5% | Increase views 25, 40% | High | Within 48 hours |
| Save rate < 5% of views for 10+ days | Professional re-photography + staging refresh | Lift saves 30, 50% | High | 3, 5 days |
| DOM > 1.5× area median + no offers | Price reduction + targeted remarketing to buyer pools | Accelerate to sale | High | Immediate |
| Strong saves but low showings | Lower price or improve showing instructions / lockbox access | Convert interest to tours | Medium | 2, 4 days |
| Good views / saves but few offers | Review offer feedback themes; consider seller concessions (rate buydown, closing costs) | Encourage offers | Medium | 7 days |
| High views on Zillow but low on Realtor | Syndicate refresh + minor description A/B test | Broaden reach | Low | 1 week |
| Favorable market absorption (inventory < 2 mo) | Hold price or small increase if multiple inquiries | Capture upside | Low | Monitor weekly |
Staging / Presentation Quick Wins
1. Declutter and depersonalize key rooms (kitchen, living, primary bedroom).
2. Add fresh towels, plants, and neutral lighting for photos.
3. Remove dated window treatments or area rugs that date the space.
4. Boost curb appeal: mow, edge, add simple planters.
Remarketing Tactics
- Email blast to agent network and prior showings.
- Boost on social with 15, 30 second video tour.
- Target lookalike audiences of recent buyers in zip code on Meta / Google.
- Reduce price and push "price improvement" announcement across portals., -
7. Period-over-Period Trend Table
Track weekly changes to spot inflection points early.
Weekly Performance Trends
| Week | New Views (Z + R) | New Saves | Showings | Inquiries | Cumulative DOM | Notes / Events |
|---|---|---|---|---|---|---|
| , , | , , , , , - | , , , - | , , , | , , , - | , , , , | , , , , - |
| Wk -4 | [[W4 Views]] | [[W4 Saves]] | [[W4 Show]] | [[W4 Inq]] | [[W4 DOM]] | [[Launch or event]] |
| Wk -3 | [[W3 Views]] | [[W3 Saves]] | [[W3 Show]] | [[W3 Inq]] | [[W3 DOM]] | [[Notes]] |
| Wk -2 | [[W2 Views]] | [[W2 Saves]] | [[W2 Show]] | [[W2 Inq]] | [[W2 DOM]] | [[Notes]] |
| Wk -1 | [[W1 Views]] | [[W1 Saves]] | [[W1 Show]] | [[W1 Inq]] | [[W1 DOM]] | [[Notes]] |
| Current Wk | [[Curr Views]] | [[Curr Saves]] | [[Curr Show]] | [[Curr Inq]] | [[Curr DOM]] | [[Latest actions]] |
Trend Diagnosis: [[e.g. "Views declining week-over-week. Saves stable. Action: price adjustment and photo refresh recommended."]], -
Sample Filled Example, Hypothetical 3-Bed / 2-Bath Listing
Property: [[123 Maple Grove Lane]], [[Springfield]], [[State]] [[12345]]
Type: Single family, 3 bed, 2 bath, 1,650 sq ft
Asking: $[[349,000]]
List Date: [[2026-05-01]]
DOM at report: [[42]]
Portals:
- Zillow: [[https://www.zillow.com/homedetails/123-Maple-Grove-Ln-Springfield-ST-12345/[[ZPID]]]]
- Realtor.com: [[https://www.realtor.com/realestateandhomes-detail/123-Maple-Grove-LnSpringfieldST_12345/[[RID]]]]
Portal Metrics (snapshot [[2026-06-12]])
- Zillow: 2,840 lifetime views, 312 last 30d, 187 saves (6.6% save rate), DOM 42 vs area median 28
- Realtor.com: 1,910 lifetime views, 201 last 30d, 104 saves (5.4%), same DOM
- MLS tracked: 47 showings requested, 11 feedback entries (common notes: "great yard, kitchen dated")
Comps Summary
- Median closed $/sq ft (adjusted): $[[198]]
- Subject list $/sq ft: $[[211]] (6.6% premium)
- Price-to-market: [[108]]% of reconciled ARV $[[323,000]]
Absorption: 3.8 months inventory, seller's market segment.
Funnel: 4,750 combined views → 291 saves (6.1%) → 47 showings (16% of saves) → 2 offers (4.3% of showings). Below benchmark on showings-to-offers.
Photo/Desc: 22 photos, 48s avg time on page (median 62s). Description 210 words, keyword-light.
Actions Matrix Applied (example):
- Trigger met: DOM 42 > 1.5× median. Action taken: [[3% price reduction to $338,500 on 2026-06-10]]
- Additional: [[Professional twilight photos scheduled for 2026-06-14]]
- Remarketing: [[Social boost live; agent open house announced]]
Weekly Trend (last 3 weeks): Views dropping 18% week-over-week before reduction; saves holding; post-reduction first 48h shows lift in 7d views projected.
Next 7-Day Watch Items: Monitor new saves post-reduction; if <25 new saves by day 7 consider further adjustment or concessions., -
How to Use This Report
1. Share the full digest with the seller along with the recommended price action and timeline.
2. Update portal data weekly or after any material change (price adjustment, new photos, open house).
3. Log actual offers received and feedback in the conversion funnel section for trend tracking.
4. Export key tables for listing presentations or CMA packages.
Data Sources and Limitations
Portal metrics are self-reported or scraped from public/agent dashboards and may vary by cookie, login state, and syndication lag. Absorption and comp data derived from MLS aggregates and public records as of the report date. This analysis is a performance diagnostic tool for marketing optimization and is not an appraisal or guarantee of sale price or timing., -
Agent Action Checklist
1. Pull fresh portal stats every Monday.
2. Compare DOM and save rate against this report's benchmarks.
3. Execute one high-impact action from the matrix if triggers met.
4. Re-photograph or restage if time-on-page or save rate lag.
5. Document all price changes and resulting metric shifts in the trend table.
> ⚠️ Template example, not professional (legal/financial/medical) advice. Figures and benchmarks are illustrative and must be verified against current local market data and portal reporting tools. All variable values appear as [[Token Name]] placeholders., -
Sources / References (illustrative as of mid-2026):
- Typical residential listing funnel benchmarks derived from aggregated industry reports (National Association of Realtors, portal data studies).
- Absorption and inventory methodology follows standard MLS market statistics definitions.
- Price per square foot and adjustment practices align with common broker CMA procedures.
(End of report, 312 lines when rendered with sample data tables.)
Illustrative preview - your actual result is built from your inputs.
How it works.
Listing Performance Monitor: provide listing URLs, portal stats, market data and get a complete listing performance digest in minutes - including views/saves trends, benchmark comparison, price-reduction triggers. Free AI workflow, no signup required to preview.
Listing performance digest with portal metrics, market benchmarks, and action recommendations.
What good looks like.
What it must include
- 01Per-listing portal metrics (views/saves on Zillow, Realtor.com, MLS), showing count and feedback, days on market vs. area median
- 02price-to-market and price-per-sqft comps
- 03absorption/months-of-inventory context
- 04conversion funnel (views to showings to offers)
- 05photo/description performance
- 06recommended actions (price reduction, staging, remarketing)
- 07period-over-period trend
Signals of expertise
- ★Benchmarks DOM and view/save rates against the local market, computes a showings-to-offer funnel, and ties recommendations to absorption rate and comp data
- ★flags listings with high views/low showings as a price problem
Common mistakes
- ×Listing raw view counts with no benchmark or funnel
- ×no market context (DOM/absorption)
- ×no actionable recommendation
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