We live in a data-saturated society. When it comes to creating intimate customer experiences, using available technologies is key to using this data. Arguably, Post offices not only have access to some of the most lucrative customer’s data but as trusted service providers are in the enviable position of being able to use it.
Retail and eCommerce have been enhancing the customer experience for a long time. Loyalty programs, for example, are a time-honored tradition that can increase revenue by well over 25%.
While some post offices may have similar programs in place for business accounts or commercial accounts, there are few, if any, programs available to the everyday consumer. However, data analytics, AI, and machine learning technology can offer an in-road to creating such a program.
But where do you begin?
Analysis of retail behavior at the consumer level can determine key areas that can be turned into upselling opportunities. Analytics can identify trends in buying and shipping behavior which, through the clever and strategic use of technology, can then be used to create incentive-based programs.
Loyalty programs are just one area where technology can help build a better customer experience. Using the available data, we can also start to predict customer behavior. Using the Escher customer engagement platform, we can start to collect real-time feedback from the point of sale level. Are customers satisfied with their experience? Did they have a long wait time? Was the clerk knowledgeable?
Over time, we can start to paint a picture of the customer experience. We can then take this retail experience data from the point of sale transaction and line it up with other transaction data. What are the customer’s purchasing these days? What does their typical behavior look like?
eCommerce professionals have been keyed in on this for a long time. There’s a reason why online retailers suggest certain purchases to you. It is based on your individual buying behavior as well as identified trends in larger buying groups.
When you use these apps, your behavior is recorded and analyzed. It then creates a predictive model of that behavior and suggests offers, discounts, awards, promotions, or deals.
Postal operators can offer a similar experience to their customers. For example, if a consumer typically buys stamps on Thursdays or ships large packages on Fridays, they can use that data. Retail clerks can then have access to that information and when that same customer arrives on Thursday to mail a parcel, the clerk can ask if they’d like some stamps today. On the app side, push notifications can be tailored to this behavior as well, i.e. “It’s Thursday, do you need stamps today?”
Similarly, AI and machine learning can help clerks provide more efficient service to the customer regarding less common processes. Cross-border shipments, for example, can be a more involved process. AI and machine learning programs can automate parts of this process, auto-fill certain fields, and identify the challenges associated with these shipments before running into troubles.
Altogether, it creates a more efficient, painless experience for the customer.
Self-service kiosks may take the human element out of the retail experience. However, that doesn’t mean there aren’t opportunities for data collection and analysis. Data, such as how often a customer hits a particular button or how often they cancel and start over, can be pulled from self-serve systems. Facial recognition and voice recognition software can also identify frustration from the customer.
This data can be pulled together to improve automated roadmaps and make machines a bit easier to navigate for the customer.
Enormous amounts of data are being collected every day by post offices. Putting this data to good use is a key step in creating more intimate, positive customer experiences. By doing so, post offices can retain a larger number of customers, increase loyalty at their branches, and improve overall customer satisfaction.
To learn more, listen to the Postal Hub Podcast featuring Wayne Haubner, CTO of Escher, as he shares his thoughts on AI, machine learning, loyalty programs, customer engagement, digital onboarding and more.