The Magic of Personalized Product Recommendations

Some days, it feels like we have stepped onto the pages of a sci-fi novel. Improvement in AI technology is progressing at such a pace that it can be difficult to wrap one's head around what is actually going on. AI is revolutionizing every aspect of business along the value chain. But what exactly do these changes mean for the day-to-day? AI can generate personalized product recommendations for each of your prospective storage customers. We have tripped off the tech jargon and marketing speak and are left with three practical examples of how AI product recommendation can improve your customer satisfaction and boost sales.

Personalized Unit Advisor

Scenario: A potential customer is browsing the website of a self-storage business.

The system, using AI algorithms, can consider various data inputs to extrapolate which unit type is most likely to suit the needs of the customer. The algorithm will take into consideration browsing history, past interactions with ads, types of units viewed, time spent on each webpage or website section, search queries used, etc., to determine the needs of this particular customer and select the most suitable from the list of available units. In practice, this would look like this: The system notices that the customer spent the most time browsing climate-controlled, large-sized units. The system will also factor in the customer has been looking at how to store antique furniture safely in the long term. Based on these inputs, the AI chatbot can proactively reach out to the customer and suggest one of the larger, climate-controlled units.

Many storage customers struggle with selecting the right unit type and size. A proactive and personalized recommendation makes the process quicker and more strategic for them. A lead who has had a positive interaction with a business is much more likely to become a customer.

Dynamic Pricing

Scenario: The system identifies a recurring visitor who is checking prices but has not booked any units.

Dynamic pricing is used successfully in the airline and tourism industries to maximize profits. It has the same potential in self-storage. AI can analyze large volumes of data almost instantaneously and make adjustments to prices based on real-time demand factors. This benefits both the customer and the storage business. For example, the system identifies that the potential customer keeps checking the same unit type. It can make a limited-time special offer to encourage the customer to book. As a result, the customer will feel valued and special. For the business, converting more hesitant customers means that the return on marketing spend improves. Dynamic pricing also helps optimize the occupancy rate. Lowering the prices for less in-demand units can help fill them.

Personalized Offers for Add-On Services

Scenario: A new customer has just booked a unit and will move in soon.

Upselling and cross-selling services are great ways to generate ancillary revenue and improve profitability. Offering additional services after a sale is no new trick. But being able to personalize the offer – is. Depending on what the customer is going to store, the AI can suggest different options. For seasonal items, like clothing, offering vacuum-compressed storage sacks and labels for rent or sale is the best option. For valuable musical instruments, insurance is the better offer. Instead of overwhelming the customer with everything, the system can suggest the one or two services that the customer is actually likely to need and buy. Again, the benefit is a better customer experience and additional revenue.

Having AI tools recommend products has benefits for both sides. For customers, it means a more effortless, efficient process with good product recommendations. For self-storage operators, it means more sales and better customer satisfaction. We hope these practical application examples have convinced you that AI can mean a smoother customer journey and a competitive edge in the changing self-storage landscape.

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The AI Frontier in Customer Interaction

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Optimising Self-Storage Operations Through Data Analysis