diff --git a/static/dashboard/index.html b/static/dashboard/index.html
index 87d7362..755d76c 100644
--- a/static/dashboard/index.html
+++ b/static/dashboard/index.html
@@ -387,18 +387,69 @@ function buildExec(fm){
``
).join('');
- // Insights
- const latestYear = fm.filter(r=>r.YearMonth>='2025-01');
- const prevYear = fm.filter(r=>r.YearMonth>='2024-01'&&r.YearMonth<='2024-12');
- const lyRev = latestYear.reduce((s,r)=>s+r.revenue,0);
- const pyRev = prevYear.reduce((s,r)=>s+r.revenue,0);
- const yoyChange = pyRev > 0 ? ((lyRev - pyRev) / pyRev * 100) : 0;
+ // Dynamic range-aware insights
+ // Split into halves for trend comparison
+ const half = Math.floor(fm.length / 2);
+ const firstHalf = fm.slice(0, half);
+ const secondHalf = fm.slice(half);
+ const fhRev = firstHalf.reduce((s,r)=>s+r.revenue,0);
+ const shRev = secondHalf.reduce((s,r)=>s+r.revenue,0);
+ const revTrend = fhRev > 0 ? ((shRev - fhRev) / fhRev * 100) : 0;
+ const fhOrders = firstHalf.reduce((s,r)=>s+r.orders,0);
+ const shOrders = secondHalf.reduce((s,r)=>s+r.orders,0);
+ const orderTrend = fhOrders > 0 ? ((shOrders - fhOrders) / fhOrders * 100) : 0;
+ const fhNew = firstHalf.reduce((s,r)=>s+r.newCustomers,0);
+ const shNew = secondHalf.reduce((s,r)=>s+r.newCustomers,0);
+ const newTrend = fhNew > 0 ? ((shNew - fhNew) / fhNew * 100) : 0;
+ const fhAOV = fhOrders > 0 ? fhRev / fhOrders : 0;
+ const shAOV = shOrders > 0 ? shRev / shOrders : 0;
+ const aovTrend = fhAOV > 0 ? ((shAOV - fhAOV) / fhAOV * 100) : 0;
- document.getElementById('execInsights').innerHTML = `
- Avg Margin ${pct(avgMargin)}: ${avgMargin >= 55 ? 'Healthy margins across the product range.' : 'Margins are under pressure — review product costs and pricing.'}
- Returning customer revenue: ${pct(repeatRevPct)} of revenue comes from repeat buyers. ${repeatRevPct > 40 ? 'Strong loyalty base to leverage.' : 'Opportunity to improve retention.'}
- Items per order: ${fmt(avgItems,1)}. ${avgItems < 2 ? 'Most orders are single-item. Bundling and cross-sell could lift AOV.' : 'Good cross-sell rate.'}
- `;
+ // Channel concentration for this date range
+ const chFilt = filterArr(RAW.channelMonthly);
+ const chTotals = {};
+ chFilt.forEach(r => { chTotals[r.ReferrerSource] = (chTotals[r.ReferrerSource]||0) + r.orders; });
+ const chTotal = Object.values(chTotals).reduce((a,b)=>a+b,0);
+ const googleOrg = (chTotals['Organic']||0) + (chTotals['Google Adwords']||0);
+ const googlePct = chTotal > 0 ? googleOrg / chTotal * 100 : 0;
+ const socialPct = chTotal > 0 ? ((chTotals['Facebook']||0) / chTotal * 100) : 0;
+
+ const rangeLabel = FSTART && FEND ? `${FSTART} to ${FEND}` : FSTART ? `${FSTART} onwards` : FEND ? `up to ${FEND}` : 'all time';
+ const halfLabel1 = firstHalf.length ? `${firstHalf[0].YearMonth}–${firstHalf[firstHalf.length-1].YearMonth}` : '';
+ const halfLabel2 = secondHalf.length ? `${secondHalf[0].YearMonth}–${secondHalf[secondHalf.length-1].YearMonth}` : '';
+
+ let insightsHtml = '';
+
+ // Revenue trend
+ if(fm.length >= 4) {
+ insightsHtml += `Revenue ${revTrend >= 0 ? '↑' : '↓'} ${pct(Math.abs(revTrend))}: ${gbp(shRev)} in ${halfLabel2} vs ${gbp(fhRev)} in ${halfLabel1}. ${revTrend < -10 ? 'Declining trend in this range.' : revTrend > 10 ? 'Growing in this range.' : 'Relatively flat.'}
`;
+ }
+
+ // New customer trend
+ if(fm.length >= 4 && fhNew > 0) {
+ insightsHtml += `New customers ${newTrend >= 0 ? '↑' : '↓'} ${pct(Math.abs(newTrend))}: ${fmt(shNew)} new customers in second half vs ${fmt(fhNew)} in first half of this range.
`;
+ }
+
+ // AOV trend
+ if(fm.length >= 4) {
+ insightsHtml += `AOV ${aovTrend >= 0 ? '↑' : '↓'} ${pct(Math.abs(aovTrend))}: ${gbp(shAOV)} vs ${gbp(fhAOV)}. ${aovTrend > 5 ? 'Customers are spending more per order.' : aovTrend < -5 ? 'Average basket value declining.' : 'AOV holding steady.'}
`;
+ }
+
+ // Margins
+ insightsHtml += `Avg margin ${pct(avgMargin)}: ${avgMargin >= 55 ? 'Healthy margins across the product range.' : 'Margins under pressure — review product costs and pricing.'}
`;
+
+ // Returning revenue
+ insightsHtml += `Returning customer revenue: ${pct(repeatRevPct)} of revenue comes from repeat buyers (${rangeLabel}). ${repeatRevPct > 60 ? 'Extremely loyal base — but dependency on existing customers may mask acquisition weakness.' : repeatRevPct > 40 ? 'Strong loyalty base to leverage.' : 'Opportunity to improve retention.'}
`;
+
+ // Channel concentration
+ if(chTotal > 0) {
+ insightsHtml += `Channel concentration: ${pct(googlePct)} of orders from Google channels (Organic + Ads) in this range. ${socialPct < 1 ? 'Social commerce is under ' + pct(socialPct) + ' — virtually zero discovery from social channels.' : 'Social contributing ' + pct(socialPct) + '.'}
`;
+ }
+
+ // Items per order
+ insightsHtml += `Items per order: ${fmt(avgItems,1)}. ${avgItems < 2 ? 'Most orders are single-item. Bundling and cross-sell could lift AOV.' : 'Good cross-sell rate.'}
`;
+
+ document.getElementById('execInsights').innerHTML = insightsHtml;
// Revenue + Orders chart
destroyChart('revOrdersChart');
diff --git a/static/offer/index.html b/static/offer/index.html
index 415d1cf..a981993 100644
--- a/static/offer/index.html
+++ b/static/offer/index.html
@@ -599,6 +599,19 @@ input[type=range]::-webkit-slider-thumb{-webkit-appearance:none;width:20px;heigh
How is this different from hiring an agency?+
An agency charges monthly for services and you own nothing when you leave. This is a one-time infrastructure build — you own the server, the workflows, the content, and the integrations. The £500/mo covers hosting and maintenance only. If you cancel, you keep the infrastructure and can self-host.
+
O
+
+
+
I build AI infrastructure for ecommerce brands — automation, content engines, and data systems. This proposal was built using the same tools I'm proposing to install. Every demo, every chart, every number on this page is real.
+
+
+
Before → After: Real Product Comparison
+ Same product. Left is the current justvitamins.co.uk page. Right is what the AI engine generates in 90 seconds.
+
+
+
Current PDP
+
+
Super Strength Vitamin D3 4000iu + K2
+
justvitamins.co.uk — actual product page
+
+
✗ Generic subtitle: "A powerful pairing"
+
✗ Single product photo (pouch only)
+
✗ No benefit-driven bullets (Feature→Benefit→Proof)
+
✗ No trust signals (money-back, UK-made, certifications)
+
✗ No price anchoring (daily cost, cost-per-dose)
+
✗ No SEO meta description
+
✗ No ad hooks or email sequences
+
✗ Cookie consent modal covers half the page
+
+
+
+
+
AI-Generated PDP
+
+
Same product — generated in ~90 seconds
+
Conversion-optimised by Gemini AI
+
+
✓ 5 AI-generated product photos (lifestyle, scale, detail, banner)
+
✓ Feature → Benefit → Proof bullet structure
+
✓ Trust bar: money-back, UK-made, EFSA claims
+
✓ Price anchoring: "just 14p per day"
+
✓ Full FAQ accordion with objection handling
+
✓ SEO meta + Open Graph tags
+
✓ 3 ad hooks + 3 email sequences
+
✓ 4 copy styles: Balanced, Premium, Direct, Medical-Safe
+
+
+
+
↑ Run Demo A above to see the full AI-generated PDP for any JustVitamins product
+
+