A 46-day, no-control-group look at what happens when a store with no conversion hypothesis simply asks leaving visitors why they're leaving.
Data as of Jul 25, 2026 · live since Jun 9, 2026 (46 days)
4,626
Total impressions
Exit-intent popup shown site-wide across all pages over 46 days
3.59%
Engaged (clicked at least one CTA)
166 of 4,626 impressions — combining 144 step-1 reason selections and 22 step-2 support-contact clicks from overlapping respondents
22
Support connections initiated
22 of the 144 respondents who selected a reason went on to request WhatsApp or phone contact in step 2
90 of 144 (62.5%)
Top feedback reason
'Other reasons' was selected 90 out of 144 times — more than the other four listed reasons combined
Store owners in unusual or specialized niches often face a version of the same problem: traffic arrives, but very few visitors take any action — no purchase, no contact form, no phone call — and there is no obvious explanation. Standard conversion-rate playbooks assume you already know roughly where the friction is. That assumption does not always hold.
This was the situation at Parham Trust Network, a retailer of networking and fiber-optic cabling equipment. The site received meaningful traffic relative to its size, but the conversion rate stayed persistently low, and the team had no prior benchmark data from a comparable business in this niche to compare against.
Parham Trust Network runs on roughly 7,000 monthly sessions, but the team could not identify why the large majority of visitors left without contacting the business or placing an order.
Most CRO case studies open with a hypothesis: "we believed X was causing drop-off, so we tested Y." This one does not, and that is worth stating plainly rather than retrofitting a theory after the fact.
The team genuinely did not know whether the problem was product range, pricing, missing product information, or something else entirely. Rather than guess and test one variable at a time, the decision was to ask visitors directly, in their own words, at the exact moment they were about to leave.
A two-step exit-intent popup was deployed site-wide: step one asks for a reason for leaving, step two offers a direct line to the support team.
When exit intent is detected on any page, a popup appears with the message "We noticed you're leaving — we'd love to know why, so we can improve," followed by five selectable reasons: couldn't find the product, prices weren't right, not enough product information, need consultation/advice, or other reasons.
After selecting a reason, the visitor sees a thank-you message and is offered a way to connect with the support team immediately — via WhatsApp chat or phone call — rather than being sent away with only a "thanks for your feedback."
Deliberately simple and broad — this campaign was built to gather signal across the entire site, not to test a narrow segment.
None of these principles are unique to networking equipment retail — they generalize to any store that has more traffic than answers.
Many store owners avoid asking leaving visitors for feedback because they fear hearing something negative. That avoidance leaves an opportunity for the businesses willing to ask anyway, since almost no competitor is doing it.
This is Alireza's personal observation, not a research-backed claim: asking a frustrated visitor for honest feedback, and visibly caring about the answer, may reduce their frustration and build trust — even when the underlying experience that frustrated them hasn't changed.
Asking "why are you leaving, so we can improve" positions the business as one that is actively trying to get better, and makes the respondent feel like a stakeholder giving input rather than just a visitor passing through.
Most feedback popups stop at "thanks for your input." This one's step 2 goes further, offering a direct path to support — turning a visitor who was about to leave dissatisfied into an active support conversation.
Across <strong>4,626</strong> exit-intent impressions, <strong>166</strong> clicks were recorded and <strong>22</strong> visitors chose to connect directly with the support team. These are engagement figures, not sales figures — see the commercial outcome note below.
3.59% (166 of 4,626)
Engaged (clicked at least one CTA)
31.95% (1,478 of 4,626)
Closed without interacting
64.46% (2,982 of 4,626)
Left without closing or clicking
The 22 step-2 clicks (WhatsApp / phone) are a nested subset of the 144 step-1 respondents, not 22 additional unique visitors — someone who picked a reason and then requested contact is counted once in step 1 and again in step 2. The rows below sum to the total click count of 166 reported in the snapshot, but represent overlapping actions from the same respondents rather than 166 distinct people.
Commercial outcome
This campaign was built for diagnostic feedback, not as a sales mechanism, and no revenue is attributed to it. The relevant outcome is that <strong>22 visitors</strong> connected directly with the support team as a result of the popup. Whether any of those 22 conversations converted to paying customers, or how much revenue (if any) resulted, is not currently tracked.
This campaign was run site-wide with no holdout group. There is no way to isolate what would have happened to these same visitors without the popup, so all figures here are engagement and attribution numbers, not causal results.
With 166 total clicks and 22 support connections over 46 days, the sample is small. A longer observation window on the site would be needed before drawing firm conclusions about reason distribution or support-conversation value.
We do not yet know how many of the 22 visitors who connected via WhatsApp or phone were converted to paying customers by the support team, or how much revenue (if any) resulted from those conversations.
The 'Not enough product information' option received only 3 of 144 step-1 clicks and appears to be underperforming as a category. Meanwhile, 'Other reasons' accounted for 90 of 144 clicks (62.5%), suggesting the real reasons users are leaving may not be fully captured by the current five choices, and the option set may need revision.
The reported 166 total clicks combine 144 step-1 reason selections and 22 step-2 support-contact clicks. The 22 are a subset of the 144, not additional unique visitors, so 166 should be read as a count of click events, not a count of distinct engaged people.
A stronger causal or diagnostic claim would require a longer live window to grow the sample, a revised reason list informed by the current 'Other reasons' volume, and integration with the support team's CRM to track what happened after each of the 22 connections.
Thank you to the Notifal team — I really liked this idea. It gave us a lot of insight into the experience customers have on our site, what growth opportunities exist, and it also deepens the connection between our brand and our customers.
When you don't have a conversion hypothesis, ask instead of guessing
Not every low-conversion problem comes with an obvious cause. Before running a series of blind A/B tests, an exit-intent feedback survey can surface the actual reasons visitors leave — directly from them, in their own words — and a second-step support offer can turn some of those departing visitors into active conversations before they're gone.
An exit-intent popup survey is triggered when a visitor's cursor behavior signals they are about to leave a page or site. Instead of a discount or offer, it asks a short question — in this example, why the visitor is leaving — to collect direct, in-the-moment feedback rather than relying on analytics alone.
In this campaign, 64.46% of the 4,626 impressions resulted in the visitor leaving without closing or clicking, and 31.95% closed without interacting. There is no control group here, so it cannot be confirmed whether the popup affected conversion behavior either positively or negatively — only that 3.59% engaged with it.
The campaign was designed to collect diagnostic feedback and open support conversations, not to drive direct sales. It resulted in 22 visitors connecting with the support team, but conversion or revenue from those conversations was not tracked at the time of writing, so no commercial figure is reported.
Yes — the mechanism (a reason-selection step followed by a direct support offer) is not specific to network equipment retail. Any store without a clear hypothesis for low conversion can adapt the same two-step structure, though the reason list should be tailored and revisited based on how often 'other' is selected.
Build the same two-step exit-intent feedback and support popup on your own site with Notifal.