The Credit Repair industry has a very well-defined audience. We are here to tell you who is more likely to convert in the Credit Repair industry. Notice we are referring strictly to “Converters,” and not just traffic.
Today’s post represents extensive research from data gathered collectively by White Shark Media over the past several years. It is not opinion-based, but rather entirely objective. If your business is part of this industry, you absolutely need to know this information in order to get the most of our your marketing efforts.
For instance, the age group between 35 and 44 years of age has an 80% probability of converting compared to just 20% from people under 24. Why would you distribute your budget evenly between the two age groups? That makes no sense. You have to allocate your budget on segments of your campaigns according to the probability these have of converting. This is the core benefit of digital marketing: full autonomy over who can see your ad, and who you are paying to look at your advertisement. But, to accomplish just that, you need to understand who these users are. Luckily, we have all the information available for free.
This data will help you increase your ROI with your PPC Campaigns dramatically.
Credit Repair — Converters
People who are looking to repair their credit have a short converting path. They do not take long to decide which company they will hire. Usually, about 84% of all converters decide to work with you on their first interaction.
In order words, the investment in remarketing would not have an ROI as high as that from targeting new users. People that visited your site last month are, most likely, already working with another company, if they didn’t decide to work with you in the first place. Then, if you were to invest in remarketing, it is highly recommended to spend most of that effort on past visitors between, at most, a seven-day time frame.
This industry is susceptible to different age groups. People under the age of 24 are too young to have bad credit as of yet. And those above 60 years of age have either good credit or care little about fixing bad historical credit.
So, 40% of all converters are between the ages of 35 and 44, followed by 25% of converters coming from 25 to 34 years old.
The great news is that every marketing platform acquires more data every year, making it easier to know which user belongs to which age group or gender. In short, we have an accurate and more extensive data available to filter our traffic.
Quick example: If you had a minimal budget, like where you have an impression share of only 20%, you may want to remove all age groups from your campaigns except for people between 25 and 44 years of age. You would, then, be allocating your budget on users that have a much higher probability of converting. You could also remove the “Unknown” category from your Google Campaigns for even better results.
Is it required to say that credit scores vary significantly across states in the U.S.?
When it comes to location targeting, we should consider the same thought-process for budget allocation. Distributing your investment according to what has a higher probability of converting.
In this case, we would not only consider what is more likely to convert, but which states have reported the worst credit scores recently. Then, if X state has the worst credit score, we would strive to bid more aggressively on that region compared to others.