How Privacy and Personalization can Work Together.

Due to COVID-19 and the issues surrounding contact tracing, I’ve received numerous questions regarding privacy as it pertains to location-based services. When it comes to privacy and personalization, most people believe that one has to be sacrificed for the other. That is simply not true. A balance can be achieved if you employ the right technology with the right strategy.

I know this sounds strange, but a technology such as LighthousePE doesn’t necessarily need to know who you are or even your name to deliver a highly personalized communications experience. By simply having a trained algorithm examine the implicit and explicit behaviors of an app’s user, it can determine what the next interaction should be. The algorithm does this though a combination of previously sent communications, executed conversions and location data. That is enough to build a behavioral profile and create a condition for the next behavior to occur. 

There is no need to choose between privacy and personalization.

As an example, let’s say you own a car washing company which also provides basic services like an oil change. The greatest value for a company like this is repeat business. Traditionally, this type of organization has relied on coupons to spur customer visits. Those coupons are not personalized. Plus, they reduce revenue every time someone turns one in. Rethink the customer journey and ideate on a new strategy. For example, on the customer’s first customer they receive a deal to come back. The next visit prompts the customer about an oil change. That visit in turn gets them a free polish and shine on their car. Each customer would get something different at this stage based on a specific need. The next visit prompts them to download your app so they can save money and receive a car care plan specific to their needs. In turn, the app delivers other content based on the behavioral data which the algorithm records. 

Here’s where the balance between privacy and personalization occurs. The behavioral platform doesn’t need to know the customer, the customer’s name or even what type of car the customer owns. As long as it knows what the time intervals are between visits and which push notifications were converted, the algorithm can make behavioral determinations. That could take the form of a reminder to get an oil change or another standard car maintenance service. It could use prompts related to the weather to spur a visit for another wash or detailing service, or even tell the customer not to come in because it’s going to rain. Location-based technology can do all of that and more while maintaining privacy.

There are a lot of opportunities you can realize with the use of anonymized data.

However, success can only occur when the technology relies on behavioral pattern recognition. Your behavioral models need to account for a customer’s motivations and their ability to perform the behavior needed. By doing that you will find there are plenty of opportunities to prompt an individual to purchase or engage in a unique brand experience at many points along the customer journey. 

Although it’s a nice gesture, placing someone’s name at the top of an email is not personalization.

Most people are happy to give up some of their personal data if it’s going to provide them with personalized experiences — 73%, in fact. But that is based on a company being transparent about what it is collecting and how the company is using that data. This means in cases where a customer signs up for a loyalty program through your app, the level of personal data now available to the algorithm can drive personalized experiences to new levels.

Achieving personalization with privacy isn’t a fantasy. It can easily happen with the right behavioral platform and communications strategy.