Research
What the research says.
Published studies, official statistics and independent reports on how local businesses win and keep customers. For each question we show what the evidence supports, what cuts the other way, and how strong each source is.
- Replying fastDoes replying fast really win customers?The best-known studies are old and come from US sales leads. Firms that tried to reach a web enquiry within an hour were far more likely to have a real conversation with the customer than firms that waited, and nearly a quarter of firms never replied at all. The popular “5-minute rule” comes from a vendor study of six firms’ phone calls that never measured sales. No peer-reviewed study yet links reply speed to sales for local businesses on WhatsApp, which is why we publish our own figures.4 sources
- WhatsApp firstWhy lead with WhatsApp in India?In India, WhatsApp is where customers already are: half of all adults use it, and three in four of those aged 18–29. It is the second most-used platform for news after YouTube. In the US only 29% of adults use it, so WhatsApp-first suits markets like India, not everywhere. Meta itself stops delivering marketing messages to people who don’t engage, so more broadcasts are not better. No independent study yet compares sales by channel.6 sources
- AI repliesShould AI answer your customers?AI that helps people reply is well supported: at a large support centre, an AI assistant raised issues resolved per hour by 15%, and by 34% for newer agents. AI replacing people is contested. Most customers say they would rather companies didn’t use AI in service, mainly for fear of not reaching a person. Angry customers react badly to humanlike bots, and how a bot is disclosed changes whether people buy. In the EU, telling people they are talking to an AI becomes law in 2026.10 sources
- Winning customers backIs keeping customers worth more than finding new ones?Keeping customers pays: in classic Bain research, cutting defections raised profits sharply at the firms studied. Emailed offers lifted spending most among customers who had lapsed, mostly without the code being used. Simple rules like “hasn’t visited in 90 days” find lapsed customers as well as complex models do. But retention alone won’t grow a business. Loyalty mostly follows popularity, contacting dormant customers can prompt them to leave, and too many messages cost money.11 sources
- RemindersDo reminders really cut no-shows?Yes. This is one of the best-tested ideas in local marketing. Across healthcare trials, reminders made people about 23% more likely to attend and cut no-shows by about a quarter, and more than one reminder beat a single one. Wording matters: telling people what a missed appointment costs cut no-shows further. Outside healthcare, reminders brought people back to the dentist and raised gym visits. Most of the evidence is from healthcare, and extra late reminders add little.7 sources
- Measuring what worksCan you trust your marketing numbers?Often not. Across 663 Facebook experiments, even the best non-experimental method overstated the effect of ads about five-fold, and eBay found its ads on its own brand name had no measurable short-term benefit. Ad effects are small next to the normal ups and downs of sales, so a single business can rarely prove what its ads return. Simple floors like promo codes help, but they undercount: most of the extra spending from emailed offers came without the code being used.5 sources
- Automating the adminDoes automating the admin really save time?For specific tasks, yes, though less than the hype. Moving tax filing online cut firms’ tax time by 40%, AI cut professional writing time by 40% in an experiment, and an AI assistant saved office workers about two hours a week on email. Across the wider economy the gains aren’t visible yet. People overestimate the time AI saves, AI drafts can take longer to check, and the one trial with small-business owners found AI advice helped strong owners and hurt weaker ones. Automate specific, repetitive tasks, check what the AI says, and measure the time saved rather than assume it.15 sources
How we choose sources
- Every figure links to its original source, and someone on our team has opened it. Popular statistics we couldn’t trace to a source are left out.
- Each source is labelled: Peer-reviewed or official (journals and government statistics), Independent research (established independent researchers) or Vendor research (companies researching their own market, shown with a label).
- We show the evidence that cuts against our approach next to the evidence that supports it.