When I was a kid and shopped with my mom, as soon as we entered the local shop, the shopkeeper would know exactly what we were there to buy.
He recognized my mom from prior visits, and he was always ready with recommendations based on previous purchases, conversations, and preferences. I viewed the shopkeeper as a friend, someone who knew my family and me, and who was there to help us. We were satisfied customers, and my mom never thought to look for another shop.
The shopkeeper achieved true customer loyalty because he made our experience feel personal, not just personalized.
Know Your Customers Before They Buy
Large corporations and e-commerce retailers have tried to replicate this small-shop experience by using new-age digital and personalized marketing techniques.
However, relying on technology to personalize brand experiences does not mean personal, human interactions are no longer necessary.
In fact, as Big Data technologies evolve, brands can get to know customers on a personal level before they make their first purchase. The data gives brands the opportunity to create more memorable, personal interactions (reminiscent of the small-town shopkeeper scenario), become a customer's companion, and improve customer experience.
Customer Data: The Key to Bringing Back the Shopkeeper Sentiment
Personalized marketing has set the expectation that companies should know consumer preferences and personalize the customer experience across all online channels. But this expectation is now extending across all channels, and even back to 1:1 human connections.
With so much data at our fingertips, achieving personalization across channels—both on and offline—is possible.
Every day, we create 2.5 quintillion bytes of data. That data is changing the way marketers are processing, implementing, sharing, and aggregating information. If analyzed properly, this data provides the potential to know customers on an individual, personal level.
Moreover, personalization means more than simply knowing customers' names; it's also about anticipating their needs. It means knowing things like preferences, availability, and location, and using this information to make targeted recommendations, That's true personalization.
Three Quick Tips
The small-town shopkeeper knows his customers because he personally interacts with them daily or weekly, and applies his collective knowledge at each future interaction.
Here are three strategies for how Big Data can help achieve the same level of customer knowledge:
1. Use context to create engaged, high-conversion customers
To facilitate conversion, introduce geolocation and contextual marketing into campaigns to deliver the right offers at the right time. No two customers are the same, and even then the same customer isn't the same all the time.
For example, one week, a 35-year-old male traveler may be en route from point A to point B for business, while the next week he's off to Vegas for a boys' weekend, followed by a family vacation a couple of weeks later.
There are so many buyer personas and preferences, but understanding how to tailor these experiences based on those multiple preferences at any point in time is what's ensuring repeat purchases, brand evangelism, and a growing marketing footprint.
And now with the introduction of the smart watches, marketers will have a whole new way to engage consumers.
2. Data can drive personalization and personalization isn't only for online
Marketers now have the ability to translate customer data into positive face-to-face customer experiences.
For example, Big Data creates the opportunity for flight attendants to have knowledge of customers' previous flying experiences, identify which customers have had negative experiences—such as a delayed flight, airline mechanical issues, or lost luggage—and offer these travelers complimentary services, such as a drink of choice, a stipend for booking travel, or Wi-Fi.
Remember to stay clear of superficial personalization. For instance, adding a customer's name to an email campaign isn't personalized if the offer has nothing to do with the customer's preferences. The same goes for online and banner advertisements.
3. Identify a new level of personalization based on behaviors and not pre-determined algorithms
We all love how Netflix and Amazon automate our recommendations for us. But to achieve this level of sophistication, companies need to invest in data engineers, analysts, and tools that harness these automated resources.
Though having the data is great, how the data is used is what truly matters. For example, marketers might have a CRM that houses contact information, and a project management system that tracks marketing campaigns, like e-newsletters, but are these two programs talking to teach other to deliver the highest level of end-to-end analysis?
Over the years, the value in marketing has extended from just delivering campaigns to building the sales pipeline.
As marketers, the role extends beyond the bottom line. With the evolution of personalization, marketers also have a responsibility to create stories and experiences that build the brand and build customer loyalty. Success starts with getting to know customers as well as we know our friends.