Why Message Mining is important for Copywriting Research - Review

Photo by Shane McLendon on Unsplash

When it comes to copywriting, you definitely should not go ahead unless, you have got your message mining right.

I am having an enriched learning experience in the Conversion Optimization Minidegree by CXL Institute.

This article is inspired by the learnings I had this week in one of the courses.

Let's start the discussion.

So, what is message mining and why it is important for copywriting research.

Let's explore these questions in the article.

What is Message Mining?

Message mining can be referred to as eavesdropping on the internet and "steal" your next killer copy for copywriting purposes.

You need to get the words from the mouth of your customers. They are the users of the product or.

So, they know exactly what pain point is getting solved by your product.

In message mining, you need to find high concentration of such copy on the internet.

CXL Institute defines it as:

"The process of scouring the internet (or other sources if available) for instances of your target customer voicing what they care most about when it comes to your product/ solution."

It is a very quick and handy way to know what your target customers are talking about when you don't have any customers yet.

Further Reading: Using Message-Mining to Pinpoint a High-converting Value Proposition for your Product

Why message mining works

The messages retrieved after message mining are the words of your customers.

They are the real users who have paid for it.

They are on the "other" side. The side where your all other potential customers exist.

So they tend to speak a language that resonates with your target market.

If you are new to market, you can instead message mine for your potential customers. Or existing customers of your competitors are talking about their product on various platforms.

It is also a useful method for those that are not that comfortable to do voice of customer interviews.

Another reason for why message mining works is that as marketers, we tend to be so biased with features of our product.

In this process, we often overlook the real value the customer could get or is getting. We also overlook the real pain point that our product is able to solve.

Converting results to Copywriting

Message mining solves two key steps in the research of your next copy.

It helps in identifying the key messages that must be in some way a part of your next copy.

Secondly, it also provides the exact copy you can directly swipe and use put forth by customers in reviews or comments.

Let's break down this further to make it more clear.

What are key messages to identify

The key messages to identify as part of the research include basically the motivation messages, value proposition messages, and anxiety messages.

Motivation messages are the desired outcomes a customer gets after using your product.

It also includes the specific pain point or problem your product solves for your customer.

It can also include decision factors before purchase. Like what prompted your customers to go ahead and make that purchase.

So you can cover both the aspects of your customer journey - The before purchase and post purchase.

Value proposition messages are something you already know about but still can eavesdrop to get it from customer's perspective.

They include the unique benefits and advantages of your product. Or, also the features that basically only your product has and gets your product super happy about it.

Then next are the anxiety type of messages. They include the uncertainties or fears that are present in customer's minds related to their upcoming purchase. The "What if" kind of messages.

So we have to ensure this anxiety type of messages are also mined as part of the process.

Swiping Customers' Copy

These include the words or phrases that you can directly take from your customers' comments and reviews.

They include, previous bad experiences with competitor's products.

Or, analogies or similarities and examples your customers relate to when they talk about your product.

These swipes can then be implemented in the heading of your next copy.

It helps to use the market slang in your copy. So people who appreciate this, will definitely relate to it and go ahead with becoming your next customers.

This can also be used to capture the emotional words.

The exact moments that can be of stress or desire that moves customers to choose your product.

5-step method for Message-Mining

Along with the what and why, I was also able to learn the how of it.

You have to follow a step-by-step process to do it the right way.

Step 1: This involves collecting the relevant keywords that are associated with your product or brand.

It may also involve keywords associated with competitor's brand.

Step 2: This step involves actual searching of your keyword followed by words like "review" or "problems".

You can do this search in major search engines like Google and Bing.

Step 3: In this step, you have to explore other websites and sources for information.

It involves searching on review sites like TripAdvisor, Amazon, Yelp and other similar sites.

Step 4: Now, we start collecting our keywords and the messages we were able to mine in steps 2 and 3.

We put them in a spreadsheet dedicated only for this purpose.

Step 5: Finally we start categorizing the messages as per their type.

Examples are motivating messages, or anxiety messages to better order them for use in our next steps.

Conclusion

Wow! That was explained so nicely in the course.

This is just the summary of my learnings.

Imagine learning directly from the expert practitioners.

So many people make it so complicated and waste time and resources and eventually do not event get their desired conversions.

We have seen in detail the importance this research has in copywriting.

Copywriting is not like any writing. Its main purpose is to sell and lead to conversions.

The more accurate and targeted our research is, the better results and conversions we can get.

The author of the article can be reached at Linkedin.