Data-Driven Decisions: Using Customer Support Analytics To Optimize Your Marketing Strategy

Today’s marketing landscape is challenging at best. There’s so much competition out there that jaded consumers tend to tune out much of the noise, making it difficult to reach them.

Add in that it’s so easy for customers to jump ship and it’s clear that we have to rethink our advertising strategy. 

In this post, the SupportYourApp team discusses a new approach. Instead of focusing on acquisition, they suggest using customer support analytics to gain deeper insights into your existing customers behaviors and preferences.

The theory being that if you can retain and delight your current clients, you improve their lifetime value to your company.  

Not only does this make more sense then trying to impress consumers who might never buy, but it also increases the chances of your customers becoming brand ambassadors.

The upside being that they’ll then refer new clients at no cost to you. 

Understanding Customer Support Analytics

With customer support analytics, you collect and analyze data for different customer interactions such as: 

  • Live chats,
  • Emails,
  • Phone calls,
  • And support tickets 

This data allows you to draw useful insights that can assist in product or service improvement and also suggest useful directions for your marketing campaigns. 

Identifying Customer Pain Points

One of the most useful insights is in identifying common customer pain points.

These might be very different from what you and your team invisage, so this is extremely valuable for your marketing team. 

Not only will your customers tell you what they do and don’t like, they’ll suggest ways to improve.

If one consumer has this issue, others may too, so you can address these pain points for more effective marketing efforts. 

Customer Segmentation

Marketers used to adopt a spray and pray approach. The days of generic marketing blasts being effective are long gone.

Customers today want you to show that you understand their unique needs, and want personalized support. 

You can use support data to more effectively segment your target customers according to pain points or previous complaints.

This allows you to offer them personalized solutions that will appeal to them.

Feedback Loops

Customer support analytics provide a valuable feedback loop for marketers.

By closely monitoring support interactions, you can see if marketing messages went over well or not. This allows you to tweak your message so that it’s more effective in the future. 

Predictive Analytics

By analyzing predictive analytics, you can predict potential roadblocks and look for ways to overcome them.

Say, for example, that historic data shows that you have a rush in support queries just before the holiday season. 

You can analyze what those queries are and put steps in place to make things simpler for your customers. Are they querying shipping charges or delivery timeframes?

Why not introduce a pop-up window to highlight these answers when they order. Alternatively, make it very clear on the order page for each product. 

You can also incorporate useful information into your marketing strategy.

For example, you could send out a mailer explaining the cut-off time for delivery by a certain date.

By being proactive, you come across as forward-thinking and can save your customers much frustration. 

Optimal Timing

Customer support analytics can also highlight useful patterns of use. For example, when customers are most likely to be active on your website or purchase.

You can use this information to optimize your marketing and outreach campaigns. 

For example, if many customers are active on your site during the weekend at a certain time, it makes sense to schedule your email marketing campaigns around this time. 

Improved Customer Retention

Having a robust customer support system can significantly reduce churn. By acting on support data, you can improve customer satisfaction and reduce frustration.

You can be proactive rather than reactive and thereby build a stronger relationship with your customers.

You can then focus some of your marketing efforts on engaging and retaining your existing customers, rather than trying to convince strangers to do business with you.

While we need new clients consistently, it’s easier to convince someone to buy when they’ve dealt with you before.

Therefore, cross-selling to existing customers may prove a more fruitful exercise. 

Closing The Feedback Loop

Incorporating support analytics is an ongoing process, rather than a one and done deal.

Your customers needs and expectations will change and you need to keep up to date with that with regular monitoring.

It makes sense for customer support and marketing to liaise closely with one another to ensure that the company meets its customers’ needs.

Conclusion

Customer support analytics offer us a range of valuable insights that can take much of the guesswork out of marketing.

When you understand your customers’ needs and behaviors better, you can create targeted, relevant marketing that is more likely to be effective.

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