Shep Hyken's Customer Service Blog

Guest Blog: Optimizing for Lifetime Value Over Transactional Customers

This week we feature an article by Josh Brown who writes about why you should focus on relational customers, how you should go about doing it, and the data you can use to enhance your initiatives and be sure your efforts are paying off. It’s important to know the value of a customer. Here is a simple guideline: Manage the interactions you have with your customers with the lifetime value in mind, with each and every interaction. – Shep Hyken

Recently, Shep Hyken sat down with Lifesize’s Chief Customer Success and Happiness Officer, Amy Downs, and discussed the importance of becoming absolutely obsessed with enhancing your customer’s experience.

Today, I’d like to talk about which customers you should obsess over.

Now, don’t get me wrong: All of your customers are important. And you should definitely do your best to provide each and every one of them with the best experience possible when they engage with your brand.

But, let’s face it:

Not every customer is going to become a loyal, raving-mad fanatic of your brand.

While some customers actively seek to build relationships with the companies they do business with, others simply want to make a transaction and go on their merry way.

So, rather than wasting tons of money, time, and energy trying to change the mindset of these transactional customers, you’re better off focusing on cultivating long-term relationships with the relational customers who do want to get more out of their experience with your company.

In this article, I’ll talk about why you should focus on relational customers, how you should go about doing it, and the data you can use to enhance your initiatives and be sure your efforts are paying off.

The Importance of Optimizing for Lifetime Value From Relational Customers

Quick question:

Which is better for your business: Having 1,000 customers who purchase from you one time in their life, or 200 customers who purchase from you five times a year, every year of their life?

In this all-too-perfect example, both sets of customers will provide the same amount of value within a single year. After that, the smaller, more loyal customer base will continue to provide value year after year – while the value from the one-off customers will have disappeared completely.

Now, those 200 hypothetical customers aren’t just going to keep doing business with you because it’s in their nature. Yes, they actively want to build a relationship with a brand that provides value to them – but you need to actually do so to keep them happy.

The most effective way to do this is to make every experience these customers have with your brand as personal and engaging as possible.

Which marketing campaign do you think would be more effective: one where you send a coupon to 10,000 random people (who may or may not be in need of your services), or one where you send a personalized offer to 500 individual consumers who have shown interest in your product?

Casting a wide net doesn’t work. First of all, most of the people who receive blanket offers ignore them. Second of all, of those that do make a purchase because of the coupon, most of them will almost certainly be one-off transactional customers. Lastly, you have no way of knowing which of your new customers are most likely to become loyal followers of your brand.

Collecting Customer Data to Personalize Your Marketing Campaigns

When researching your customers, you should aim to know as much as you can about who they are as a consumer. Your goal should be to determine:

  • What they want to accomplish by engaging with your brand
  • How they intend to use your product or service to accomplish these tasks
  • Which media channels they are most likely to be reached through

This data will help you create personalized campaigns that touch on specific pain points your prospective customers are currently facing – in turn making it more likely that your brand will catch their eye.

You can collect this data through a variety of means, from sending out customer surveys to conducting interviews (both with customers and future prospects alike).

It’s also important to keep track of how your previous marketing campaigns have affected your sales numbers and your customers’ propensity to become loyal. Consider data such as:

  • Churn Rate: The percentage of your customer base that has ceased to do business with your company.
  • Net Promoter Score: Determines the likelihood of a single customer becoming a brand evangelist for your company.

By taking an honest look at how your previous campaigns have affected these and other customer-related scores and averages, you’ll equip yourself with the ability to tweak and fine-tune your future campaigns to better resonate with your target consumer base.

Conclusion

Just as there are transactional and relational customers, so, too, are there transactional and relational businesses.

There’s nothing necessarily wrong with focusing strictly on making a sale and moving on to the next customer.

But doing business in this way surely isn’t going to set you apart from your competition in any way.

On the other hand, by focusing on truly helping your customers overcome their pain points, you’ll make a clear-cut case that your company is the go-to in your industry. In turn, not only will you generate scores of loyal fans of your brand, but you’ll also make these happy customers more likely to spread the good word about your services.

Josh Brown is the Content & Community Manager at Fieldboom, the place to create beautiful forms and surveys in less than 5 minutes. 

For more articles from Shep Hyken and his guest contributors go to customerserviceblog.com.

Read Shep’s latest Forbes Article: If I Wanted My Question Answered In 15 Hours I Would Have Waited 15 Hours To Ask The Question

Save

Save

Save

Save

Save

Save

Save

 

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes:

<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>