CRO / CX Audit Prepared for Hopewell Residential

Hopewell Residential:
Here's What We Found.

A deep-dive analysis into website performance, leveraging website analytics to provide a roadmap for improving conversion and UX.

Client
Hopewell Residential
Prepared by
clearmotive
Data Period
Jan – Dec 2025
Clarity Period
Jan – Apr 2026
Status
Final
clearmotive® × Hopewell
2026
Begin
★ Executive | Top-line narrative

Executive Summary.

Improving website conversion rate makes every dollar we invest in marketing more effective.

The site converts at 1.51% today. Improving this to 2% would generate roughly ~860 additional leads per year. Improving to 3% would generate roughly ~2,600 additional leads per year.

We analysed 12 months of data across the full HRM website, cross-referenced against four months of Microsoft Clarity behaviour data, and reviewed technical, SEO, accessibility and page-speed performance alongside. This has enabled us to identify key structural optimisations and areas of focus. We now have a catalogue of over 35 recommendations, prioritised by ease and cost of implementation and by expected impact, which can be executed over the coming year.

This analysis allows us to systematically improve the website at both a macro level, by refining the core journeys users take through the site, and at a more granular, page-by-page and element-by-element level.

Combined CVR — today
1.51%
↓ vs 2.17% peak
Sessions
176,171
Jan – Dec 2025
Total Conversions
2,660
Type A 996 · Type B 1,664
Monthly Conversions · Type A vs Type B · 2025

GA4 event counts · Jan – Dec 2025 · Annual totals: Type A 996 · Type B 1,664 · Total 2,660

Our priority for recommendations prioritises higher-intent conversions such as booked appointments, quote requests and holds, as opposed to more passive conversions such as email signups.
⚡ Quick Wins | Ship before end of May

Four Things You Can Ship Before End of May.

Some of our findings should be easy to fix or adjust, and should start driving immediate impact without significant dev or design investment.

🔗
Connect Show Home cards to detail pages Dev · small
Cards currently have no link to detail pages and no "Book a Tour" CTA. Images are dead clicks. 29% mobile dead-zone rate. Single fix, direct line to 0.11% Type A CVR on 13,926 sessions.
📧
Fix email UTM attribution Marketing ops
Email traffic is likely mis-attributed in GA4 (UTM or iOS MPP). A major channel is flying blind; fix = accurate attribution with zero dev work.
🔁
OpenConnect form ID + UTM tracking Analytics
318 contact submissions with "(not set)" form ID. Fix tracking first, then L2S data will tell you whether OpenConnect earns its keep or gets retired. Don't decide blind.
💰
QP affordability copy + inventory urgency Content
QP is the right product for the affordability market, but the page doesn't say so. Price anchors, "move-in ready" framing, inventory signposting. No dev, content-only.
◆ Primary Strategic Insights | Where the biggest gains live

Primary Strategic Insights.

We uncovered a huge amount throughout this project — here are the strategic observations we believe will have the highest probability of CVR impact.

🏠
The Quick Possession journey underperforms vs New Homes by over 50%
🎯
CTA architecture and placement will provide an opportunity to minimise traffic loss throughout user journeys
📣
Implementing paid-media optimised landing pages will improve conversion performance and increase engagement
🏷️
We need to develop a strategy of how to communicate promotions throughout the user journey without diverting from it
📝
Conversion type/form hierarchy on key conversion pages will provide significant benefit
Section 01 | Findings

Objective, Introduction & Methodology.

Approach, data sources, and the problem we're aiming to solve.

The gap

Combined CVR sits at 1.51%, which is at the lower end of peer benchmarks of 1.7 – 2.5%. Even small gains here will drive significant impact on lead volume, sales volume and cost / sale.

Current Combined CVR
1.51%
↓ vs 2.17% peak
Target CVR
2.5–3%
Old-site peak: 2.17%
Total Site Sessions
176K
Jan – Dec 2025

Terminology

  • Conversion Rate (CVR): The percentage of website sessions that contain a conversion action, booking an appointment, requesting a quote, filling in a contact form, or signing up for emails.
  • Type A conversions: Internal nomenclature for higher-intent conversions, quote requests, holds, and booked appointments.
  • Type B conversions: Internal nomenclature for passive conversions, email signups, calls, and general contact form completions.

The Objective

Thoroughly review user behaviour on the website, using both quantitative data from web analytics and qualitative data from heatmapping and session-recording technologies, to identify any and all potential improvements that can be made on the site. Once recommendations are validated and reviewed, we catalogue and prioritise them based on ease/cost of implementation and expected impact, providing a clear roadmap for how to drive CVR from 1.51% to 2% and beyond.

Methodology

We leveraged the GA4 API, enterprise-grade AI tools, and user-behaviour tracking software (Microsoft Clarity) to provide a comprehensive data layer for the website. It's worth noting that Clarity was only fully implemented in mid-2025, while the GA4 data analysed was for the full year of 2025. However, there's ample data in both sources to provide statistically significant, data-backed recommendations.

Data Gaps and Caveats

  • Some web forms were implemented after our previous tracking implementation project, meaning we don't have perfect end-to-end data for these conversions as we do for the majority. This is minimal, but worth flagging.
  • We excluded data from October's promotion as it skewed the overall data significantly and painted an inaccurate picture of what's really happening.
  • Email marketing isn't being correctly UTM tagged; it's very likely that much of the traffic categorised as "direct" on the site is coming from Hopewell's email efforts.
  • Clarity does not allow heatmaps on page elements that collect PII (personally identifying information) such as email addresses; therefore we have minimal data on form performance. We'll need to run A/B tests to evaluate form performance.
  • Although we used Pardot/Salesforce data for high-level analysis of which conversion points drive to sale most effectively, we did not dive deeper into lead → sale data due to time, privacy and budget constraints.
  • Changes have been made to the site after the date range analysed, however nothing significantly affects the analysis here.
  • Analysis is limited to the HRM site and does not include analysis of community sites.
Section 02 | Findings

Site Performance Overview.

High-level traffic, device split, geography, and source breakdown.

Total Sessions
176,171
Jan–Dec 2025 · Traffic Acquisition
Type A Conversions
996
0.57% CVR
Type B Conversions
1,664
0.94% CVR
Monthly Average
~14.7K
Sessions / month
Device Split (GA4)
176K
Sessions
Mobile 62.2%
Desktop 36.3%
Tablet 1.5%
Mobile CVR 1.52%
Desktop CVR 0.79%
Traffic by Source / Medium

GA4 default channel grouping · Jan–Dec 2025 · 289K channel-attributed sessions

Demographic Breakdown · Age + Gender
Awaiting fresh GA4 pull
Run Scripts/ga4_extract_demographics_city.py locally; sandbox can't reach the GA4 Data API. Output will land in Raw Data/ and this chart will populate.

Sessions by age × gender · GA4 (Google Signals identified ≈19% of users) · 25–34 leads, 35–54 the core homebuyer band

Traffic by City
Calgary
138.3K
Edmonton
19.0K
Toronto
11.4K
Vancouver
10.0K
Airdrie
6.4K
Other AB
51.4K
Other / RoW
78.1K

By GA4 city dimension (Jan–Dec 2025) · Calgary dominates · "Other / RoW" includes ≈15K preview-bot traffic (Lanzhou, Ashburn, Boardman, etc.)

The site received, on average, just under 15,000 monthly sessions throughout 2025. The huge majority of traffic comes from within Alberta. On average, the site generated around ~83 Type A conversions per month and ~139 Type B conversions per month.

The site has quite a typical channel breakdown, with much traffic coming directly or through branded search (i.e. users who already know who Hopewell is through reputation), alongside high volumes of paid traffic from continual advertising investment.

Mobile devices account for just under 65% of overall site visits, and the site converts slightly better on mobile than desktop across all key conversion points.

Which conversions actually fire

We have 10 different types of onsite conversion, with much higher frequency on some than others.

Type A · High-intent 996 events 0.57% CVR on 176,171 sessions
Get a Quote
624
Book Appointment
358
Request Lot Info
8
Request a Hold
6

Two forms account for 98.6% of Type A conversions. Hold is functionally invisible despite the highest L2S rate on site; see CA-5.

Type B · List-building 1,664 events 0.94% CVR on 176,171 sessions
Email Signup
1,648
Registration
16

Email signups significantly dominate Type B conversions. Registration has the site's best L2S rate (13.7%) but only 16 events; same "high-quality form, invisible surface" problem. 60% of email sign-ups come from /calgary/perks-promos.

Section 03 | Findings

Page-Level Performance.

Where on the site do users convert?

Reading this table: three things to know first:
  • Content groupings: we used regex strings to group together specific page types such as Product Pages where there are dozens of instances of similar pages.
  • There are some pages which should be treated as informational, or navigational, and shouldn't be evaluated on their own direct CVR, but instead as to whether they're providing the information the user is looking for and/or clearly driving users where we want them to go.
Page URL Tier Sessions Type A A CVR Type B B CVR Total CVR
HomesSearch Single Tier 1 57,528 116 0.20% 42 0.07% 0.27%
Product Page (New Home) Pattern Tier 1 42,589 526 1.24% 41 0.10% 1.34%
Communities (landing) Pattern Tier 1 40,223 5 0.01% 166 0.41% 0.43%
Calgary Hub Single Tier 1 39,250 2 0.01% 373 0.95% 0.96%
Quick Possession (QP) Pattern Tier 1 30,822 165 0.54% 23 0.07% 0.61%
Homepage Single Tier 2 19,152 0 0.00% 0 0.00% 0.00%
Show Home Listing Single Tier 1 13,926 16 0.11% 7 0.05% 0.16%
Virtual Tours Pattern Tier 2 11,124 0 0.00% 25 0.22% 0.22%
Show Home Detail Pattern Tier 1 10,139 71 0.70% 5 0.05% 0.75%
Promos Single Tier 2 9,790 16 0.16% 457 4.67% 4.83%
Contact Single Tier 2 3,702 11 0.30% 91 2.46% 2.76%
Gallery Single Tier 2 2,540 0 0.00% 2 0.08% 0.08%
Hopewell Advantage Single Tier 2 689 0 0.00% 2 0.29% 0.29%
Other pages (Edmonton Hub, blog, lp, legal/info) Pattern 62 418
Site total (Events HRM, Jan–Dec 2025): 996 0.57% 1,664 0.94% 1.51%
Key Insights:
  • Our Product Pages drive the highest volume of Type A conversions — however there's significant disparity between New Home, Quick Possession and Show Home Product Page CVRs.
  • The Promos Page drives the best volume of Type B conversions, which is great. However, we need to review how to incorporate promotions within the onsite user journey as it currently diverts users.
  • Pages such as Calgary Hub and HomeSearch don't convert well, but they're not meant to. However, even though they're primarily pass-through/navigational pages, that doesn't mean we shouldn't look to optimise them.
Section 04 | Findings

User Flow Analysis.

Why the search page is so critical, and evaluating user flow across the site.

There's a clearly defined route to conversion on the site: Homepage → Calgary (or Edmonton) Hub → Home Search → Product Page → Conversion. However, only ~15% of users take this ideal journey; they get distracted or exit throughout the experience.

The huge majority of Type A conversions come from product pages. Over 90% of product page (both NH and QP) visits come directly from the search page. Therefore, ensuring that both search and product pages are as optimised as possible will be the most impactful optimisations we can make.

QP inbound via HomesSearch
89.1%
of internal routing
NH inbound via HomesSearch
91.8%
of internal routing
Calgary Hub → Product direct
0%
Communities: 0% · Homepage: 0%
Page Flow Diagram (Sankey, GA4 Jan–Dec 2025) Filter to isolate a single product flow.

Key Insights

① Criticality of Home Search

Over 90% of Product Page visits come from the Home Search page. Two implications: (a) search functionality should be as friction-free and user-friendly as possible; (b) we should consider enabling ways for users to get to product pages directly, further up in their journey.

② New Home vs Quick Possession

Quick Possession product pages get proportionally fewer clicks from the Home Search page, and they convert less well than New Home Product Pages. This is a HomesSearch-side asymmetry, not a QP-page issue alone.

③ Paid Landing Pages

We drive paid traffic to mid-funnel pages (e.g. Home Search), which aren't optimised for cold traffic. We should consider building paid-media-specific landing pages that provide newly-landed users with more context.

④ Promos Page

The Promos page is highly signposted throughout the user journey. Although most users do come back to the desired funnel, it would be more optimal to include promotional messaging within the journey, not pulling users to a separate, non-conversion-optimised page.

Quick Possession Funnel: a clear opportunity

QP is the primary conversion gap, not a site-wide problem. NH is already above target. Three compounding causes.

QP Type A CVR
0.54%
165 conversions / 30,822 sessions
NH Type A CVR
1.24%
526 conversions / 42,589 sessions, above 1.0% target
The QP → NH gap
−0.70%
same funnel, different product, different outcome
① HomesSearch chokepoint

89.1% of QP product-page traffic arrives via HomesSearch. Per-listing click-through is 42% of NH cards (2.4× gap). Half is inventory mix (75 QP vs 133 NH URLs), half is per-listing treatment. → PL-8.

② Paid-traffic mismatch

A higher proportion of QP traffic arrives directly from paid campaigns on the homesearch page, which isn't ideal for users landing cold on the site. We should consider developing paid media landing page templates.

③ Quick Possession Product Pages

QP Product Pages broadly mirror the NH Product Pages. There are several opportunities to optimise these page templates without needing to entirely redesign them.

Promos: a loop, or a leak?

This page converts well, but 32% of users drop out of the funnel here.

Promos outbound returning to funnel
68.1%
9,515 total outbound · 6,480 back to Calgary Hub / HomesSearch / Product / QP
Promos inbound from funnel
87%+
HomesSearch + QP + Calgary Hub dominate inbound (12,830 users)
The pattern

Users detour to /calgary/perks-promos mid-journey, scan the current incentive, then loop back into the funnel to keep shopping. However, ~32% of users don't return to the core journey.

Two implications:

  • Embed promo content inline on Calgary Hub, HomesSearch filter results, and Product Pages; users are already detouring to check the deal, and surfacing it contextually removes the detour without losing the message.
  • Don't get rid of the page. 60% of General Registration form submissions (13.7% form → sale CVR) come from this URL. However, it's not a high-volume page, and it's not high-converting. The page itself should be optimised to pull users back into the funnel, and we should prioritise it less earlier in the funnel.
Strategic framing. Promotions are critical to conversion, especially in the current economic environment. Hopewell's promotional structure isn't simple, which makes it challenging to push personalised promotional info to users throughout the journey. At the moment, although the Perks & Promos page does push people back to product or search, we still see some drop out entirely. Finding ways to give users the promo info they need without pulling them to a separate page will be valuable and should eliminate funnel leakage; optimising the page itself to pull users back to the intended flow will also be highly beneficial.
05

Page-by-Page Findings

12 pages in funnel order, grouped Tier 1 (conversion funnel) and Tier 2 (support / content). Each tile opens a full analysis: GA4 performance, conversions detail, Clarity interactions, insights, and recommendations.

Click a tile to open the full page analysis, metrics, conversions, top onward paths, interaction breakdown, insights, and recommendations. Source: GA4 (Jan–Dec 2025) + Microsoft Clarity (Jan 8–Apr 7, 2026). Cross-references are directional only, different time windows.

Tier 1 — Conversion Funnel7 pages, the core path to conversion

Tier 2 — Support & Content5 pages, not primary conversion drivers

06

UX Deep Dives

UX deep-dives into the most important pages on the site

07

Satellite Experiences

This section provides analysis around two "satellite" sections of the site, Virtual Tours and OpenConnect, that sit beside the main funnel rather than within it.

Virtual Tours Shortlisting tool

11,124 sessions across 79 tours. Direct CVR looks near-zero, that's misleading.

VT Sessions
11,124
Jan–Dec 2025
Tours Active
79
Across product pages
Return to Product Page
32.5%
After VT exit

The Virtual Tours aren't intended to be a direct conversion tool. They drive solid volume and engagement, however, only 32.5% of users return from the Virtual Tours to the product pages. When users exit the Virtual Tour, it should be more clearly signposted how to return to their product exploration.

OpenConnect Tracking gap

Home personalisation / configurator — not a chat widget. Strong engagement, broken attribution.

OC Session Starts / Year
6,198
~517 / month
Stay 1min+
92.5%
27.8% questionnaire completion
Contact Submissions
318
L2S unknown, "(not set)" form ID

Around 3% of sessions include OpenConnect. It does engage users very well — 93% of those sessions spend more than 1 minute within the experience, and 28% complete the questionnaire.

However, the core question is how well it affects sales, and because the form within Pardot has not been configured separately, we don't know whether it accelerates or detracts from sales compared to the standard experience.

It's also highly possible that this functionality could be replaced by a well-designed live chat feature, which would be less immersion-breaking and offer additional CX functionality.

Recommendations:
  1. Categorise the form correctly in Pardot.
  2. Gather data and evaluate lead → sale impact.
  3. Demo and investigate suitable live chat software.
08

Foundations

SEO, technical, page speed, and accessibility, the substrate everything else sits on.

SEO Opportunities 14 recs

Ensuring search and answer engines have the information they need to rank us

Brand Traffic Dependency
82%
High risk
Keyword Gap vs Mattamy
12.5×
Indexed keywords
Recommendations
14
On-page & Technical

We ran a high-level SEO audit to identify on-page and technical opportunities. While we've worked on content generation in the last 12 months, there are some on-page and technical fixes which will support the CRO optimisations recommended here.

IDItemEffort
SEO-3Optimise /calgary title tag + meta for generic homebuilder terms (186k impressions, pos 32)Quick
SEO-5Add H1 tags to 43 pages currently missing them (likely product listing templates)Quick
SEO-6Fix 11 duplicate title tags — each page needs a unique, keyword-targeted titleQuick
SEO-2Audit and fix 49 broken (404) pages — recover wasted link equityQuick

Technical Recommendations TECH-1 → 9

Updates to site technical foundations. While these are adjacent to direct CRO work, they'll improve site performance, data accuracy and UX.

IDItemEffort
TECH-1URL query string cleanup (legacy indexed URLs)Medium
TECH-2Pardot form name audit, stop "(not set)" leakageQuick
TECH-4Show Home card links, connect cards to detail pagesQuick
TECH-5Popup frequency capping + page-level rulesQuick
TECH-6OpenConnect form ID + UTM attributionQuick
TECH-7GA4 event param standardisationMedium
TECH-8Root redirect attribution note (/ → /calgary)Quick
TECH-9Email UTM attribution fix (iOS MPP / tagging)Quick
Technical Overview

These recommendations are indirectly related to CRO — but will improve overall site performance and UX, as well as data hygiene and reporting accuracy. The majority of them are relatively low-lift fixes which can be implemented by the dev team.

Page Speed 3 URLs · Apr 28 2026

PSI snapshot for Calgary Hub, HomesSearch, and the Product Page template, desktop and mobile, field (real-user CrUX) and lab (Lighthouse).

Field CWV, Real Users
4 / 6
Passing, 2 CLS-driven failures
Lab Score, Mobile
28–35
Desktop range: 52–59
Worst Mobile LCP (Lab)
26.1s
Calgary Hub · slow-4G simulation
Calgary Hub /calgary
Desktop Pass55 LCP 1.7s · TBT 1.16s · CLS 0.05
Mobile Fail34 LCP 26.1s · TBT 1.08s · CLS 0.13
Top opportunities
  • Improve image delivery, 1,096 KiB savings (mobile)
  • Reduce unused JavaScript, 827 KiB
  • Render-blocking requests, 120–170ms
  • Layout shift culprits + forced reflow
HomesSearch /calgary/homes/search
Desktop Fail52 LCP 1.8s · TBT 1.31s · CLS 0.16
Mobile Pass28 LCP 10.1s · TBT 1.45s · CLS 0.30
Top opportunities
  • Reduce unused JavaScript, 787 KiB
  • Render-blocking requests — 200–300ms
  • Layout shift culprits — desktop field CLS 0.43
  • Use efficient cache lifetimes, 190 KiB
Product Page /…/new-home/Dion
Desktop Pass59 LCP 1.9s · TBT 1.73s · CLS 0.00
Mobile Pass35 LCP 18.1s · TBT 1.19s · CLS 0.00
Top opportunities
  • Improve image delivery, 1,353 KiB savings (mobile)
  • Reduce unused JavaScript, 463–805 KiB
  • Render-blocking requests, 150ms
  • Forced reflow + network dependency tree
Site Speed Overview

These reports pull from a simulated 'lab' environment on 4G. In reality, users are unlikely to see these kinds of load times.

We've bundled some core recommendations into our technical recommendations matrix and will work with the dev team to prioritise alongside other recommendations.

Accessibility 92/100 · 3 Lighthouse failures

Overall score strong. Contrast, heading order, and missing main landmark flagged. Plus 6 inferred risk areas.

Lighthouse Score
92
/ 100
Hard Failures
3
Contrast · Heading order · Landmark
Inferred Risks
6
Beyond automated checks
Accessibility Overview

We do have strong accessibility scores; however, there are some core areas where Lighthouse (Google's accessibility tool) has marked us down. These have been included within the recommendations matrix, and we'll work with the dev team to prioritise them accordingly.

09

Recommendations Matrix.

All 78 active recommendations across the catalogue and technical recommendations. Sort by any column, filter by status / effort / impact / section, search across titles & evidence, click any row for full detail.

Showing 78 of 78
Effort
Impact
Section
ID Title Section Effort Impact