Quais são as maneiras mais eficazes de segmentar e segmentar clientes existentes para programas de retenção e fidelidade?

When we talk about behavior-based segmentation in B2B marketing, we can understand how the customer uses a product or service, what features are most useful, how they interact with support, usage metrics, areas of the client's company that engage most with a certain feature, main channel used, onboarding metrics, among other factors. On the other hand, in a D2C context, we focus more on the individual behavior of consumers. This includes interactions on social media, purchasing behavior, purchase history, communication preferences, channel preference, etc.

Behavior-based segmentation is in my books the right way into segmentation. In B2B it is generally acknowledged that at any given time, only 5-10% of your TAM is in the market for your product. What if you knew when your key accounts moved into the consideration phase? This is where intent data come into play. Being able to identify intent signals will help you prioritize your marketing spend, and perhaps even more importantly, direct Sales to approach the customers right when they are moving from the top layer of the funnel, into the consideration phase. When you combine 1st party data with data from your own martech stack, you are one step ahead of the competition. That is actionable segmentation.

This quite good I would also include how they respond emotionally to products or services, which is the real thing behind the behavior patterns. People are emotional beings and we buy through emotion. How does the product and service make us feel? Does it reduce stress, make life easier and enjoyable? Can I really feel a tangible impact the product is having on my life?

Don't forget new customers! First impressions matter and if you do not have a clear segment and strategies for your new customers they likely won't see the value in what you are offering and ultimately are less likely to build a habit around your product and become loyal.

This is also good advice, I would just focus not to overdo it, since people are receiving too many messages and emails nowadays. Striking balance is key. In addition, the headline and copy of those messages or emails have to intrigue and connect with them on a deep emotional level. People are getting too many promotional materials and many never feel like it's written by someone who truly understands their challenges, struggles and desires. So in the midst of all the look-alike stand out, create your own unique voice that is tailored to your clients true needs.

If you can reliably predict their preferences and needs from past behaviour do that! Too many companies are asking for information they already have and it makes customers less likely to want to engage. If there are data points that you need explicitly from the customer, be sure to communicate why you are asking, how they will benefit from giving you this information and how you will keep their preferences private and secure!

🧐 I have yet to see a more actionable and simple segmentation than RFM. And you? It clearly categorizes all customers into the right segments and it gives you comprehensive information about the state of your customer base. And if you visualize it as a 3x3 matrix, it's a great way to track it in static and dynamics on dashboards

In the case of D2C CRM (It also serves for B2B), RFM analysis is the first step in terms of value segmentation. The logic here is to think of the customer base as if it were a "portfolio". The money saved on low-value customers, in the long run, pays for the implementation of programs for high-value customers. We call this strategy the "Barrier Strategy". We protect our best customers from other customers and the rest of the organization. We don't leave our high-value customers exposed to mass marketing initiatives. The whole company communicates with the high-value customer using a single speech. And the first step to reach this level of strategy is RFM analysis.

It is incredibly hard to predict the long-term value of a customer accurately. This is even more difficult/ impossible for new customers who don't have enough history of purchase and engagement. The best way to understand the potential value of your customers is to model their current behaviour against your existing base and look for specific signals that they are exhibiting the early signs of high or low-value customers. Just remember even with the best modelling it's hard to truly predict customers so ensure you have pathways for them to graduate to higher segments. For example, show them a variety of prices and offers.

This is kind of grey line here. It's not black or white. Some lower tier clients may decide to suddenly go up a tier due to a sudden change in their personal or business needs, and they might choose you because they know you for a while and know the value you offer(either through your insightful contents or other activities.) Building true, emotional and meaningful relationships is key here.

This is good. I would also add having data on how much or how frequently they use the platform, service or product. This could also be an important metric.

Value-based segmentation is a start. But don't go patting yourself on the back yet. You need to look at which customers are likely to leave and how much will it cost you to get them to stick around. You might not need to spend on the VIPs. If their future business is in the bag, there isn't much sense in tossing retention budgets at them. Instead, roll up your sleeves and do some additional segmentation work. Look at who's likely to walk across your whole customer base and experiment to see how expensive it is to intervene to keep them. Keep their lifetime value in mind and optimize your efforts accordingly.

In my experience, the best place to start is to understand your customer journey. How do they come across your products, what is their first impression, what are those first few experiences like and what keeps them coming back? Customers are loyal to brands that understand their needs! They want a personalized experience that helps them achieve their goals. Segmentation is an internal business exercise the customers want to see the end result of that without feeling like they were put in a bucket with a lot of other customers.

All models are wrong but some are useful. Many orgs make the error of focusing purely on those they assume are high value, committing to a short term value extraction and long-term revenue risk. With the tech available today, sure, identify segments, but also explore lookalikes to expand your revenue pool, and automate and scale activities with them. Then use your time to expand the scope of your ops, fix blind spots, and nurture more segments. Or focus on a small subset and take them from 10% to 10x : and templatize learnings that you can scale to other customers. Creating this second loop will help you win the now and create high value models for later. A dynamic segmentation strategy isn't an objective but a pre-requisite.

It's good advice, except that it lacks personal or human touch and emotional considerations. Additionally, having real-life examples of business or companies doing what's suggested will make it more engaging and relatable.