Marketers are always looking for ways to deliver messages that are more effective and personalized to their customers. Whether you’re trying to push specific brands and product lines or promote new product categories to the customers for which it’s most relevant, being able to identify the right customer and deliver a curated message is a critical - but challenging - capability.
For starters, building highly targeted segments is time consuming and requires valuable technical resources from data science, IT or engineering. Once built, there is manual effort required to load the segments created in one system to all of the other channels of engagement like email, website, custom applications, social media and more. Finally, by the time you activate your segments across channels they are already out of date. For example, I may have been likely to buy a pair of jeans today, but if I buy 3 pairs tomorrow and marketing doesn’t receive their “High propensity to buy jeans” segment until the weekend, that segment is no longer relevant.
It is critical in modern day loyalty marketing to use dynamic real-time segmentation to orchestrate the right experience at the right time, across systems - without delay. Customer Engagement Hubs, like Usermind, are built to tackle this exact problem. With a Customer Engagement Hub, you can activate audiences easily and in real-time. They eliminate the human and system costs to generate segments and move them from where they’re built to where they need to be activated across a mix of channels.
A Customer Engagement Hub allows you to evaluate segment members in real-time. This means when a customer exhibits a specific behavior, you can immediately assign them to one or more segments that match the defined criteria in second. This allows you to engage with them immediately, instead of waiting for customer data to be collected and aggregated into a data lake and then waiting for the lead to journey through the segmentation process, creating a delay of hours to even days.
A great example is the way Usermind can build a customer service segment of “any customer who has contacted customer service more that 3x in a month and spends more than $1M/year”. A customer who spends $1.5M/yr contacts help desk via chat bot or email for the 3rd time in a month. Usermind receives the signal for the defined “at risk” criteria and in seconds that customer is added to the segment, triggering a message to both the chat bot and the customer service system (Zendesk) to put this customer in a high priority queue for a customer service rep to reach out.
Once you’ve enabled real-time segmentation, you can take your programs and experiences to a new level by incorporating machine learning models from your data science team. The problem for most marketers today is those models are often black boxes that they can’t tweak or control to deliver specific and differentiated customer experiences. With an orchestration layer, the Marketing team will have the power to incorporate machine learning models with prescriptive rules to both control and improve how models built by data science teams are used in customer journeys. For example, a clothing retailer is planning to promote new Spring arrivals from three of their most popular brands. Their data science team has an intent model that scores a customer based off of their affinity towards their most favorite brands. The marketing team uses that model to select customers above a defined threshold for the 3 brands - but a smart marketer also knows there are two new brands that are very similar (by style, demographic, price point, etc.) to the three brands. The team creates a rule to additionally include customers who have scored high for those two new brands in this campaign, increasing reach and impact. This ability to join machine learning models and human intelligence and intuition drives greater engagement and subsequently revenue.
Customer Engagement Hubs are becoming essential for marketers to deliver the right message and the right support at the right time. Customers have come to expect a certain quality and relevance in the experiences their brands deliver. Real-time segmentation is necessary to deliver just that, and has the added benefit of reducing human time and potential error scrubbing and uploading data manually. Once you achieve real time segmentations as a marketing org, your Customer Engagement Hub allows you to take those customer experiences to a new level, pairing machine learning and human intuition to drive the right experience, increase reach and engagement and ultimately drive more revenue.