Helping you make a smart decision
At CardGuru, there is a science behind what we do. We do not want your credit card search skewed by bias. We want to provide you full transparency into the inner workings of CardGuru and how we come up with our star ratings. We want to give you the facts. To do that, we have created multiple algorithms that weigh specific factors when assigning star ratings. These factors are related to each card's primary features.
What we found to be most important while creating these algorithms was simple: you.
What does the average American consumer spend their money on? Which cards will help them on their financial journey? Which cards have above average benefits? Below, we will outline the ranking methodology behind these algorithms and the decisions we make to help you make better choices.
The Basic Formula
Every card's features are analyzed based on data that investigates Americans' average spending versus the defining characteristics of a card. For our basic algorithm, we look at these factors:
Cashback cards receive their own algorithm that factors in what the average American consumer spends their money on versus how much a card could potentially pay out the most in rewards. To do that, we looked at America's spending habits. What do we spend most of our money on? In case you were wondering, here's that list:
- 41% – Everyday Spending/Bills
- 20% – Dining
- 15% – Grocery
- 9% – Entertainment
- 8% – Gas
- 4%- Travel
- 2% – Department Stores
- 1% – Airfare
With this data in mind, we cross-referenced potential cashback for each card. Would it be worth it, based on average spending habits, to obtain this cashback card?
Balance Transfer Formula
The Balance transfer algorithm is one of the simplest. We look at 3 factors:
- Its introductory APR must be 0%
If it's not 0%, we don't classify it as a balance transfer card and don't rate it as such
- How long is its intro period? (in months)
The longer the intro period the better. Typically ranges between 6-18 months
- The balance transfer fee (in percentage)
Typically ranges from 0% – 5%
After collecting these data points for each card, we do the simple math to calculate which cards are actually worth recommending to you.