Conversion Research Sprint
Funnel analysis, session replays, heatmaps, on-site polls and user tests across your top revenue templates. Output is a ranked list of friction points with revenue attached.
Same traffic, more orders — tested on the things Houston buyers actually get stuck on: search, specs, quotes and reorder.
Delivered remotely for brands across Houston and Texas.
Most CRO advice is written for a DTC apparel store with 400,000 monthly sessions. That is not the typical Houston client. The typical Houston client has 30,000 sessions, an average order value in the hundreds or thousands, a repeat rate that would embarrass a subscription brand, and a conversion problem sitting entirely inside a search box that cannot resolve a part number with a dash in it.
That changes the method. With lower traffic and higher order values, revenue per session moves faster through structural fixes than through button colour tests. So the programme starts with instrumentation and research: session replays of buyers who searched twice and left, the internal search log nobody has opened, and the ten most common questions your counter staff answer on the phone.
Then testing, properly run. Pre-declared sample sizes, no calling a test on day three because it looks good, and quote submissions and account reorders counted as conversions rather than only card checkouts. Losing tests get reported in the same detail as the winners, because most changes do not work and a programme that only ever shows you wins is not measuring anything.
In a metro whose commerce runs on technical catalogues, on-site search is the storefront. We consistently find Houston stores where a third of sessions touch search, half of those searches return zero results, and nobody has ever read the log — buyers typing a manufacturer part number the store stocks but has indexed only in a PDF spec sheet. Fixing synonyms, cross-references and dash-and-space handling in a search index routinely beats a full redesign on revenue per session. The second recurring leak is the quote path: buyers who need terms hit a card-only checkout, bounce, and phone the order in to a competitor with a request-a-quote button. Both are Houston-shaped problems, and both are testable.
The same standard of work we run for every client — applied to a Houston brand’s realities.
Full service detailFunnel analysis, session replays, heatmaps, on-site polls and user tests across your top revenue templates. Output is a ranked list of friction points with revenue attached.
Every hypothesis scored on impact, confidence and effort, with the projected revenue and required sample size stated up front. You always know what runs next and why.
Tests built and QA'd across devices, browsers and your app stack, with flicker-free rendering and no measurable hit to Core Web Vitals.
Pre-declared sample sizes, sequential-testing guardrails and segment-level readouts by device, traffic source and new versus returning. No peeking, no calling a test at 80%.
Cart drawer, shipping thresholds, payment options, express checkout placement and post-purchase upsell, tested against AOV and revenue per session rather than clicks.
Tests run, results in full, cumulative revenue impact and what the results taught us about your customers. Losers are reported in the same detail as winners.
We do not work off a rate card. Every Houston engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.
Get this scopedWe instrument the funnel properly first. Most stores have broken or double-counted events, and you cannot optimise against numbers you cannot trust.
Quant tells us where visitors leave. Qual tells us why. We combine analytics, replays and direct customer input before writing a single hypothesis.
Hypotheses are scored and sequenced so the highest-value, lowest-effort tests run first. The roadmap is shared and you can reorder it.
Two to four concurrent experiments depending on traffic, each run to a pre-declared sample size. No test gets stopped early because it looks good on day three.
Winners get hard-coded into the theme, losers get documented, and every result feeds the next round of hypotheses. The programme gets smarter each month.
Anonymised under NDA. Figures pulled from the client’s own analytics.
8-figure DTC brand, ~140 SKUs, US + CA · Shopify Plus (migrated from Magento 2)
Magento 2 cost $9k a month in hosting, extensions and emergency dev before a single feature shipped. Mobile LCP sat at 5.4 seconds and mobile converted at less than half the desktop rate across 68% of sessions. The named constraint: 11,412 indexed URLs and a top-3 organic position on their hero category, so a migration that lost rankings would cost more than the platform ever saved.
~$6M/yr DTC, 900+ SKUs across size and colour variants, US · Shopify Plus
Returns ran at 31% and refund cost consumed the entire paid media margin. One size chart image served 40 different fits, and 62% of add-to-carts started on a collection page that never showed variant availability. The named constraint: no new product photography budget, so every fix had to come out of the existing asset library and the review corpus.
“We'd been running our own tests for a year and calling every 3% swing a win. The first thing they did was tell us our sample sizes were garbage, which was not a fun call to sit through. Six months later we're getting wins that actually hold up when you re-measure them. Sitewide CVR went from 1.9% to 2.7%.”
Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.