Standard items and experiences are not good enough for the contemporary consumer: people are increasingly attracted to personalized items and tailored services.
Let’s just look at product trends. From 3D printing, which enables any Jack and Jill to design and produce their own unique items in virtually no time, to wearables that respond differently to each single person’s body and needs, customized items have gained more and more prominence in the market.
And it’s not just products. People have also come to expect that their shopping experience be tailored to their requirements and preferences.
If you are a retailer, this puts you in a pickle. The problem is, you can’t just get up one morning and decide to do personalization. In order to offer tailored items and services, you must be able to collect, analyze and correctly assess customer data. You need an effective strategy, and the right tech.
It’s all about the data
To begin with, you need to collect data on your customers – lots of it. “You can never have too much data – bigger is definitely better,” Werner Vogels, Amazon’s chief technology officer, told the BBC. “The more data you can collect, the finer-grained the results can be.” And Amazon knows more than most about data and personalization: in the words of David Selinger, chief executive of RichRelevance, specialized in content personalization, “in 2004, Amazon had better data capabilities than most retailers do today.”
The good news is, you can get that data pretty easily, as consumers are ready and willing to provide personal information to retailers.
- A Microsoft research showed that 40 percent of global consumers want brands to track and analyze data to optimize their shopping experience.
- In an eMarketer study, more than 50 percent of consumers said they bought more items from retailers that suggested products based on their browsing and buying history.
- According to a BlueHornet report, 75 percent of shoppers expect emails from companies they do business with to be personalized based on their online purchases and browsing behavior.
Putting all the information together
Having data is unfortunately not enough. One of the biggest challenges for retailers lies in linking data from multiple sources to customer profiles. Virtually every shopper is now active – browsing, researching information, buying – across different channels. If you can only track your customers in one channel, you may end up offering them a partially personalized experience – for example, giving suggestions of clothes in their size on your e-commerce website, and then sending them emails featuring items that have nothing to do with the customer’s tastes and shopping history. You may be tempted to think that some personalization is better nothing – but you’d be wrong. By partially tailoring your communication you will give a disjointed view of your brand, and may even risk compromising the whole effort. To offer a wholesome brand experience, you must target your customers throughout their journey, across the touchpoints.
Start by implementing ways to gather information: for example, you could add a sign-in to your e-commerce portal. Do not forget to give users something back in exchange for their personal information: for example, enable logged-in users to save products to a wish list, and to add items to their shopping cart across devices.
Tech can help you bridging the gaps. Successful retailers use integrated retail management systems that connect the different sales channels, enabling them to see all their sales and customer data in real time in the system, no matter if they come from the POS, the e-commerce website and the loyalty app. This kind of knowledge can bring great advantages: Lush, the cosmetics retailer, has been using real-time data stats to optimize their store layout. Employees in Lush stores have been changing the position of specific items based on the specific store’s sales data, placing close together products that have proved to sell well in combo.
Breaking it up
Once you have an idea of your customers’ profiles, segment them into groups. Divide them by lines which are relevant for the products you sell: age, gender, location (climate can be a very important factor if you for instance sell apparel and fashion). Do not forget to look at shopping history: you probably shouldn’t send an ad for a luxury diamond-encrusted timepiece to customers who usually buy plastic watches from you — and vice versa.
Let’s put it in context
What time of the day does your customer usually shop? What shopping items are available in his local store, or can be delivered free to his address? Has your customer changed location? All these contextual factors can be very important when it comes to delivering a meaningful, personalized shopping experience. If a customer who used to log in from Hawaii to order bikinis and shorts has recently changed delivery location to London – that’s a warning bell for you not to use last year’s shopping history for personalized offers.
Get a help from technology
Thankfully you don’t have to do all the data analysis on your own. There are now powerful and readily available tools that retailers can use to crunch customer data and get actionable suggestions. Microsoft’s Machine Learning Studio, which Microsoft Technical Program Manager Luis Cabrera introduced last year at conneXion, is one of these services. Just upload your data to the Microsoft web service and run the analytics model that best fits your research question. You can run various analyses, depending on your goal: better understand your audience, forecast product demand, or create to-the-point, personalized recommendations for customers.
There are major opportunities open for retailers who have the data, and know how to use it.
Big Brother? No, thank you
Personalization is great, and we all want companies to recognize us as a valued shopper – up to a certain point.
Imagine this: you are on a trip abroad, and enter the physical location of an online shoe store where you often shop. The staff member at the door greets you by name “Good morning, Mr. Chang! Welcome to New York!” What would your first thought be?
- Oh wow, great personalized service!
- How on earth do they know my name and where I’m from?!
The scenery above is technically possible, as long as the customer is using a loyalty app, and the store has installed beacons. Even though technology enables you to go this far, most people would find this level of personalization excessive, and probably borderline creepy.
Even if you don’t go these lengths, make sure you keep some boundaries. People often like browsing unnoticed, and don’t want to be immediately identified across channels. Ultimately, the goal of personalization is to make people feel like a celebrity, not like the unwilling protagonists of a reality show.