diff --git a/docs/research/SBE-TECH-USE-SURVEY-2026.md b/docs/research/SBE-TECH-USE-SURVEY-2026.md new file mode 100644 index 0000000..a0a7ea3 --- /dev/null +++ b/docs/research/SBE-TECH-USE-SURVEY-2026.md @@ -0,0 +1,83 @@ +# SBE Council Technology Use Survey — March 2026 + +**Status:** provisional research note (session 2026-09-15) +**Source (opened this session):** https://sbecouncil.org/wp-content/uploads/2026/03/SBE-Technology-Use-Survey-March-2026-Final.pdf +**Fielded:** February 17–23, 2026 · **n=517** small business owners (2–99 employees) · TechnoMetrica for SBE Council · credibility interval ±4.4 pp + +## Why this note exists + +Fresh (2026) category-level signal on how US small businesses use AI, marketing, and sales channels — used to pressure-test GeoLocal wedge, entry paths, and later free/silver/gold packaging. **Not** a ranked brand list of local SaaS apps (that remains unavailable from this source). + +## Caveat (scope) + +Sample is general SMB 2–99 (professional services, construction, tech, retail, etc.) — **not** local-only / brick-and-mortar filtered. Figures may skew differently for salons, bakeries, and similar local genres. Report does **not** mention Google Business Profile, Apple Business Connect, Bing Places, or local SEO by name. + +## Key findings (sourced) + +### AI adoption + +| Finding | Figure (from source) | +| :--- | :--- | +| Use ≥1 AI tool | 82% | +| Median AI tools in use | 5 | +| Confident adopting AI/digital tools | 90% (52% very) | +| AI important to competitiveness/growth (among users) | 81% (41% very, 40% somewhat) | +| Expect major or transformative industry impact | 53% | +| Median annual AI spend | $2,200 | +| Plan to increase AI spend next year | 62% | +| AI in >25% of operations | 32% (8% in >half) | +| Top AI uses | Research 37%, content 30%, marketing automation / project mgmt / social each 25% | +| Primary AI guidance sources | Peers 45%, internal tech staff 38%, associations 37% | +| Top barriers to further AI | Knowledge/training 23%, privacy 17%, cybersecurity 13%, cost 12% | +| Non-users: “see no need” | 62% of non-users | +| Median owner hours saved / week via AI | 5 | +| Median employee hours saved / week via AI | 11.5 | +| Revenue gains attributed to AI | 66% (22% >10% gains) | + +### Marketing & sales channels + +| Finding | Figure (from source) | +| :--- | :--- | +| Use social media marketing | 64% | +| Rely on word-of-mouth | 58% | +| Email marketing | 42% | +| Paid online advertising | 35% | +| Highest reported ROI channel | Social 34%, then WOM 24% | +| Platform importance (income/branding) | Facebook 62%, Instagram 43%, YouTube 36%, LinkedIn 29%, TikTok 26%, Amazon 24% | +| Median share of sales from digital/e-commerce | 20% | +| Digital platforms make competing with larger firms easier | 74% | +| Sales channel mix | Website 53%, social 51%, brick-and-mortar 37%; median **3** channels | +| Largest revenue source | Own website 30%, social selling 23%, storefront 14%, online marketplaces 13% | +| Majority of revenue from offline (≥51%) | 31% | +| Plan to add sales channels next year | 47% | +| Median annual digital ad spend | $3,290 | +| Plan to increase digital ad spend (12 mo) | 43% | + +### Firmographics (context) + +| Finding | Figure (from source) | +| :--- | :--- | +| Median employees | 12.2 | +| Median 2025 revenue | $684K | +| Median business age | 8.5 years | +| Location type | Commercial office 38%, home office 27%, retail 7% | + +## Implications for GeoLocal (session synthesis — provisional) + +1. **Owner-AI entry path is timely.** High AI tool count + confidence supports “owner (or their AI) asks how we get discovered” as a real GTM surface alongside web chat. +2. **Discovery gap.** AI use clusters on research/content/social — not Core 3 listings. GeoLocal’s free checkup fills an unexamined foundation layer. +3. **Peer/WOM GTM.** Peers are the top AI guidance source; WOM is a top marketing channel. Shareable audit proof + partner referral fits the trust path better than vendor-first cold ads. +4. **Spend context for later bundles.** Median AI (~$2.2k/yr) and digital ads (~$3.3k/yr) set a ceiling/context for silver/gold — still pin bundles after value-prop angles are captured. +5. **Hybrid local reality.** Website + offline + multi-channel remain central; Discovery foundation (NAP + Core 3 + hours) sits under that, not instead of it. +6. **Knowledge barrier = free wedge.** Top barrier is training/knowledge; free audit + ranked punch list attacks “I don’t know what to fix” and “AI doesn’t apply to me.” + +## Explicit non-findings + +- No ranked brand list of local SMB SaaS (QuickBooks, Square, Toast, etc.). +- No Core 3 / Maps / GBP schema or usage metrics. +- Do not treat category % as local-genre gospel without a local-filtered source. + +## Related POR + +- `docs/strategy/BUSINESS_PLAN.md` — north star, wedge, owner workflow, tiers +- Packaging free/silver/gold: **pinned open** until value-prop angles are fully captured