Retail Marketing: Using Technology to Drive Personalization at Scale
We’ve heard that personalization should be at the core of retail marketing strategy. Does this mean that you send discounts on jeans to previous customers who bought jeans? Yes, that’s a part of it, but there is so much more. Every touchpoint needs to make the customer feel like they are having a one-on-one conversation with you. However, from a business standpoint, your strategy needs to be scalable as well. The question then becomes about balancing scalability with that personal touch.
Interested in learning more about Bob’s talk on personalized retail marketing? Catch a recap of his keynote from WE Prosper Summit 2019.
How Can You Scale Personalization?
Platforms are disrupting every industry. Retail marketing is no different. In fact, platforms can enable you to achieve personalization at scale. They are able to do this by focusing on three elements:
- Experience Disruption- creating a frictionless customer experience that makes everyone pivot. Eg: AirBnB made it so convenient to find the comfort of home in a new city that people started to prefer them to hotels for certain types of trips.
- Business Model Disruption- changing the value chain or existing business models to find an advantage. Eg: Dollar Shave Club cut out other players in the value chain and went direct to consumer. By doing this, they were able to keep costs very low and provide value and convenience to their customers.
- Technological Disruption- when technology enables you to take leaps, speed up innovation or benefit from convenience. Eg: Amazon’s Redshift platform- a new business could use this to launch themselves into the market in a matter of days
These disruptions all allow retail marketers to personalize their offerings. For instance, experiences can be curated to meet customer preferences. Similarly, value and/or convenience can be factored in based on what is most important to each customer segment. With the help of technology, these offerings can remain customized but can be scaled as businesses grow.
What do Retail Customers Want?
When it comes to retail, customers know what they want. They want personalization & control. This means that they don’t just want to be offered a multitude of choices. Options generated by retail marketing should cater to their preferences. Furthermore, they want to be in control of their journey and the information you hold about them. The statistics speak for themselves:
- 45% of consumers left a website due to being overwhelmed by too many options
- 82% of customers are willing to share data- as long as there is transparency, control, and service
- 79% of consumers have never felt a brand was too personal or invasive
- 81% of consumers will shop more if you recognize, remember, and make relevant recommendations
- 75% of consumers want to control their journey
If you’re in retail marketing, the data above shows you that listening to your customers is a large part of the exercise. Let them educate you on how best to serve them.
How can Retail Marketing Address Customer Wants and Needs?
Think service design: a dynamic service experience is critical to getting 1:1 personalization. Customer experience should be designed in such a way that every touchpoint must feel personal. Focus on three elements to develop this design:
Personalized Shopping: Stalking is Not Personalization
You have several kinds of data at your organization. You don’t have to track your customer’s every move or stalk them in order to get insights. Personalized shopping can be driven by combining different types of data- both your own and that acquired from third parties.
You can use transactional or historical data + shared intent by the customer + insights from machine learning that can provide inferred intent. These three combined can provide actionable insights and be powerful to drive personalization. Further, your communication can be more proactive through these.
For example, your customer may have bought entry-level luxury handbags before. You then notice that they add a high-end luxury bag to their cart and abandon it there for some time. This shows you their intent or preparedness to spend on a big-ticket item. Using data science, you can analyze similar patterns among other customers to predict the value of their next purchase or even predict the likelihood of a big-ticket purchase on their next transaction.
When you have this kind of insight, you can send them tailored offers- maybe a personalized shopping experience in-store or a promotion offered specifically around high-end handbags.
Personalized Merchandising: Profiling is Not Personalization
Data and machine learning are powerful tools in retail marketing, of course. Data-driven segmentation can also help you refine personalization. However, even the best algorithm may not be enough to create something highly personalized. Applying human intuition on a digital platform is what will get you there.
For instance, let’s consider the previous example. Your predictive model indicated that the customer is ready for a luxury purchase in their next transaction. However, as a seasoned retail marketing professional, you may realize that the bag remaining in their cart is a sign. Your instinct can take you from prediction to anticipation. Prediction is about retailers being in control, but anticipation puts the control back in the hands of the customer. In this case, your experience tells you that the customer is hesitant about making such a big decision.
Knowing how likely they are to make a purchase empowers you to approach them with personalized merchandising. You may send them a video about craftsmanship on the brand of handbags they are interested in. Thus, you showcase the value of the product to them. On the other hand, you may realize that they are ready to make a luxury purchase but maybe the handbag is a bigger commitment than they are ready for. In this instance, personalization could be in the form of promotions on belts, wallets or other smaller items from the same brand.
Personalized Advisor: Chatbots are Not Personalization
Retail consumers seek experts just like anybody else. They are looking for personalization in the form of advice. While chatbots are a nifty solution to interact with customers at scale, they cannot replace real advice.
In the spectrum of virtual to real experts, there are three archetypes that are typically used in retail marketing.
Retail marketers are pivoting towards 1:1 personalized orchestration engines. These are not just about sharing advice but also listening to your consumers.
For instance, when a customer is shopping online your recommendation engine may be showing them similar products. However, customers seek advice more than recommendations. You can drive personalization by showing them how to pair the item they are looking at with others or how to style it for different occasions based on their lifestyle.
You could also offer advice in the form of answering frequently asked questions about the product. This can go beyond product specs to show how the product functions in different settings, how durable it can be, etc.
Thus, you can build personalization into the entire customer journey. By listening as much as recommending, retail marketers can ensure that customers control their own journeys.
Top 4 Retail Marketing Takeaways:
Here are four top takeaways from Bob’s talk on personalization in retail marketing.
- Consumers don’t mind that you have data on them. In fact, they preferred to be recognized and offered relevant offers. But, they want transparency and control over the data.
- Combine your knowledge of your customers with data science to gain insights.
- Become proactive in your communications, open yourself up to listening to your customers. Go from predicting customer behavior to anticipating it.
- Retail experiences need to be personalized in every step of the customer journey. In order to achieve this in a meaningful way, you need to combine technology and human instinct.
Catch a Recap of Making it Personal
Watch the full recap of Making it Personal, presented at WE Prosper Summit 2019.