Right, so I sat down with Edward the other day, a real whiz when it comes to AI and marketing, to pick his brain about something that’s been buzzing in my head: how can small, local businesses use the power of personalised recommendations to really compete with the big boys? We’re talking about that personalised product/service recommendation powered by, well, in this case, AI and data analytics. It’s not just about knowing what someone bought last time; it’s about anticipating what they need and want next. Think about your favourite coffee shop knowing you always order a flat white with oat milk and suggesting a new vegan pastry they think you’d love. That’s the kind of magic we’re aiming for.
First, we tackled the data dilemma. Edward explained that it’s not about having massive datasets like Amazon. Local businesses have something arguably more valuable: local data. Think about it: your point-of-sale system, loyalty programs, online booking systems, even social media engagement – all goldmines waiting to be tapped. “The trick,” Edward said, leaning forward, “is finding affordable and accessible tools that can actually make sense of it all.”
He suggested looking at cloud-based AI platforms that offer pre-built models for recommendation engines. These are often pay-as-you-go, so you only pay for what you use, making them much more budget-friendly than building something from scratch. One crucial point he stressed was the importance of focusing on ethical considerations and data privacy. Customers need to trust you with their data, so transparency is key. Make sure your privacy policy is clear and easy to understand, and always ask for consent before collecting and using personal information.
Next, we talked about understanding your target audience. This isn’t just about demographics; it’s about understanding their motivations, their pain points, and their aspirations. “You need to go beyond just analysing purchase history,” Edward explained. “Look at their social media activity – what are they liking, sharing, and commenting on? What are they talking about in online reviews?” This deeper understanding allows you to create recommendations that are genuinely relevant and helpful, rather than just generic suggestions.
Edward then launched into some innovative ideas to use AI for business growth. “Imagine,” he said, “a local bookstore using AI to recommend books based not just on genre, but on the reader’s past reviews on Goodreads or their engagement with particular authors on social media. Or a restaurant using AI to predict what dishes a customer might like based on their dietary restrictions, past orders, and even the current weather!” The key, he emphasised, is to tailor the recommendations to the local context and community. What are the local events, trends, and preferences? How can you incorporate these into your recommendations to make them even more relevant and appealing?
Engagement is also critical. It’s not enough to just present recommendations; you need to make them engaging and interactive. Edward suggested using personalised email campaigns, push notifications, or even in-store kiosks to deliver recommendations in a way that’s visually appealing and easy to use. The language is critical too, consider the voice of your target audience when generating the recommendations. Make them conversational, personable and relevant to each individual.
Edward gave a final piece of advice on measuring the impact of your AI-powered recommendations. “Track key metrics like click-through rates, conversion rates, and customer lifetime value,” he urged. “This will help you to understand what’s working and what’s not, and to continuously improve your recommendations over time.” This is an important point; the ability to iterate and improve based on data is what makes all the difference.
So, to recap, the journey to unlocking AI for SMBs begins with accessible and affordable AI tools. The next step is understanding customer data, including online behaviour and purchase history. The focus should be on creating engagement strategies that involve consideration of audience and tone. Finally, we must keep measuring performance and iterating based on results to improve the models over time. This entire process ensures that value is delivered. In short, it’s all about leveraging AI to understand your customers better and offer them more relevant, valuable experiences, thus driving business growth while prioritising ethical considerations. That’s a win-win for everyone.
