Next Best Action (NBA) is an essential use case for creating next-generation customer experiences, as it enables companies to personalize their interactions with customers in real-time to improve engagement and satisfaction.
What is next best action?
Next best action refers to the use of data and analytics to determine the most appropriate action to take with a customer at a given time based on their individual needs and behaviors.
The core questions a next best action model answers are:
- What should we do/say/offer?
- How should we deliver this?
- When should we do it?
Which types of data are used for next best action?
The data used can be of any type:
Transactional: has a purchase been made and of what amount?
Demographic: where is the user from? What income bracket are they assumed to be in? etc.
Behavioral: the sum total of the user’s activity on your site or app: clicks, views, page visits etc.
The most predictive data type is behavioral data, as there is no better predictor of our future actions than what we have previously done. It stands to reason that where someone is from is less likely to influence their actions than their past behavior.
A warehouse-first approach to next best action
With a warehouse-first approach, data from sales, the customer office, marketing, and finance is centralized in your storage location and then modeled and used to predict the next action your company should take with a consumer.
Once this is achieved using advanced analytics, machine learning and AI can more accurately predict the right content, message or offer.
The benefits of next best action
The reason NBA is so important to next-generation customer experiences is that customers today expect a high level of personalization from the brands they interact with. They want to feel understood and valued as individuals and expect companies to provide them with relevant and timely information and offers. By using data and analytics to determine the best course of action for each customer, companies can create a personalized experience that meets these expectations.
In addition, NBA can help companies achieve their goals, such as increasing sales or reducing customer churn. By delivering the right offer or message to the right customer at the right time, you can increase conversion rates and strengthen customer loyalty. NBA can also help companies optimize their resources by focusing on the highest-value customers or opportunities.
Why choose Snowplow for next best action?
Snowplow is a Behavioral Data Platform, built specifically for capturing the smallest details of user behavior and sending this data to your storage destination in a highly-usable format.
We specialise in helping companies create ultra-predictive data sets for AI and advanced analytics. These data sets offer a level of insight that can differentiate you from the competition.
The data hits your warehouse or lake AI- and BI-ready, freeing your data team from endless wrangling and preparation and allowing them to conduct sophisticated experiments to maximize engagement.
Here are some of the features of Snowplow which help you to reengage more customers:
- Robust user identifiers: Snowplow provides out-of-the-box user IDs, including session IDs, cookie IDs, and IP addresses.
- First-party server-set cookies: These cookies can track customers for up to 400 days (at the time of writing), including Safari users normally blocked by ITP restrictions. Snowplow is actually deployed in your own cloud environment, ensuring this is done in a highly compliant way.
- Out-of-the-box e-commerce features: Snowplow provides a set of e-commerce tracking methods and associated JSON schemas that you can use out of the box (or you can create your own custom data structures for your own specific business needs).
- 130+ metrics tracked automatically: Other metrics which can help you optimize abandoned cart recovery, such as the page the user was on before and after the event happened, the device, location, and other specific user information. Take a look at our modeled data.
- Event properties are kept within a single table: This means generating user segments to answer advanced questions is straightforward. These questions include the optimal time to send communications, what counts as an abandoned basket, and which channels to choose.
To test this for yourself, try Snowplow for free