The ultimate guide to the best credit card combinations

Whether you’re new to the world of points and miles or just looking for the best ways to level up your current card portfolio, a strategic credit card pairing is one of the easiest ways to maximize your earning potential.

You’ve likely heard of the most popular card groupings — the Chase Trifecta and the Amex Trifecta — but these are far from the only ways to combine credit cards.

Let’s discuss how different credit cards work together to boost your earning power, and go over some of the best credit card combinations.

What makes the best credit card combination?

Several factors can make a good card combination. At its core, a good pair is one in which both cards earn the same rewards but have different bonus categories. This way, you’ll be able to maximize your earnings across a wider range of purchases than you would with just one card.

Each pairing below shows how to boost your earnings with two complementary cards.

Amex Platinum and Amex Gold

The American Express Platinum Card® has a high $895 annual fee (see rates and fees) but is great for travelers since it earns 5 Membership Rewards points per dollar spent on flights booked directly with an airline or through American Express Travel® (on up to $500,000 each calendar year, then 1 point per dollar spent thereafter).

It also comes with extensive airport lounge access, plus a slew of valuable statement credits. (Enrollment is required for select benefits.)

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Card art for Amex Platinum and Amex Gold Card — THE POINTS GUY

The American Express® Gold Card is a foodie’s dream card with a $325 annual fee (see rates and fees). It earns 4 points per dollar spent on dining at restaurants worldwide (up to $50,000 in purchases per calendar year, then 1 point per dollar spent thereafter) and on groceries at U.S. supermarkets (up to $25,000 in purchases each year, then 1 point per dollar spent thereafter).

It also comes with statement credits each calendar year for dining and takeout purchases. (Enrollment is required for select benefits.)

Why they’re a great combination: These cards work great together because you’ll earn more on flights with the Amex Platinum than you would with the Amex Gold alone (5 points per dollar spent rather than 3; spending caps apply) and more at restaurants worldwide and U.S. supermarkets with the Gold than you would with the Platinum alone (4 points per dollar spent rather than 1; spending caps apply).

Additionally, the cards’ benefits and statement credits hardly overlap, meaning you’ll get tremendous value from having both cards. You can then transfer your Membership Rewards points to any of Amex’s 20 airline and hotel partners.

TPG credit cards editor Olivia Mittak likes using the Amex Gold and Amex Platinum together to maximize earnings in her top spending categories. “My grocery and dining purchases almost always go on my Gold, while I book flights with my Platinum; I also put large purchases on my Platinum to take advantage of that card’s extensive protections,” she says.

To learn more, check out our full reviews of the Amex Platinum and the Amex Gold.

Apply here: American Express Platinum Card
Apply here: American Express Gold Card

Chase Sapphire Preferred and Freedom Unlimited

The Chase Sapphire Preferred® Card (see rates and fees) is one of our favorite travel rewards cards, with its standout earning categories being 5 Ultimate Rewards points per dollar spent on travel booked through Chase Travel℠, 3 points per dollar spent on dining (including eligible delivery and takeout), select streaming and online grocery purchases, and 2 points per dollar spent on all other travel.

Additionally, it comes with some valuable travel protections — all for a low $95 annual fee.

The Chase Freedom Unlimited® (see rates and fees) is a great everyday card. It has no annual fee and earns 3% cash back on dining (including eligible delivery and takeout) and drugstore purchases and 1.5% back on all other purchases.

Why they’re a great combination: Both cards allow you to earn an impressive return on dining purchases, but you’ll earn more on your non-Chase Travel travel spending with the Sapphire Preferred versus the Freedom Unlimited. Where the Freedom Unlimited really shines is in its nonbonus spending.

By itself, the Freedom Unlimited earns cash-back rewards. However, if you also have the Sapphire Preferred, you can combine your rewards from the two cards and transfer them to any of Chase’s 13 travel partners for maximum value.

To learn more, check out our full reviews of the Chase Sapphire Preferred and the Chase Freedom Unlimited.

Apply here: Chase Sapphire Preferred Card
Apply here: Chase Freedom Unlimited

Ink Business Preferred and Chase Sapphire Reserve

The Ink Business Preferred® Credit Card (see rates and fees) is one of our favorite business cards. It earns 3 points per dollar spent on travel, shipping, internet, cable and phone services, and advertising purchases made with social media sites and search engines (on the first $150,000 in combined spending).

Cardholders will also earn 5 points per dollar spent on Lyft purchases (through Sept. 30, 2027) and 1 point per dollar spent on all other purchases.

The Chase Sapphire Reserve® (see rates and fees) is the premium sibling of the Chase Sapphire Preferred. With it, you’ll get access to Chase Sapphire and Priority Pass lounges, a flexible $300 annual travel credit and other useful statement credits.

It earns 8 points per dollar spent on bookings made through Chase Travel, 4 points per dollar spent on flights and hotels booked directly, and 3 points per dollar spent on dining purchases (including takeout and eligible delivery).

Why they’re a great combination: If you have a lot of business expenses, pairing a business card with a personal card can work in your favor. With this combination, use your Ink Business Preferred for the first $150,000 in business purchases each year and your Sapphire Reserve for travel and dining purchases to maximize your points per dollar earning opportunities across the board.To learn more, check out our full reviews of the Ink Business Preferred and the Chase Sapphire Reserve.

Apply here: Chase Sapphire Reserve

Chase Sapphire Preferred and Sapphire Reserve

Holding both the Chase Sapphire Reserve and Chase Sapphire Preferred allows you to maximize points on travel spending.

You’ll earn 8 points per dollar spent on all Chase Travel purchases and 4 points per dollar spent on hotels and flights booked directly on the Sapphire Reserve. Plus, with the Sapphire Preferred, you’ll earn 2 points per dollar spent on all other travel purchases.

With this combo, you’ll also receive valuable travel perks, such as lounge access, primary rental car insurance and travel protections.

Why they’re a great combination: Holding both cards will allow you to maximize points on travel spending, ensuring you earn at least 2 points per dollar spent on your travel purchases.

Plus, by holding both cards, your points can be used to book travel directly through Chase Travel at a value of up to 2 cents per point with the Points Boost feature (depending on the specific redemption; see your rewards program agreement for full details).

And if you really want to maximize your earnings, you could create a trifecta by adding the Chase Freedom Unlimited, ensuring you earn at least 1.5 points per dollar spent on all purchases.

Apply here: Chase Sapphire Preferred Card

Apply here: Chase Sapphire Reserve

Capital One Savor Cash Rewards and Capital One Venture Rewards

The Capital One Savor Cash Rewards Credit Card has no annual fee and is a great option for everyday spending categories. The card earns 5% cash back on hotels, vacation rentals and rental cars booked through Capital One Travel, 3% cash back on dining, entertainment, grocery stores (excluding superstores like Walmart® and Target®) and popular streaming services and 1% back on all other purchases.

The Capital One Venture Rewards Credit Card has a $95 annual fee. It earns 5 miles per dollar spent on hotels, vacation rentals and rental cars booked through Capital One Travel and 2 miles per dollar spent on all other purchases, making it a good card for spending that doesn’t fall in other cards’ bonus categories.

Why they’re a great combination: Use your Savor for purchases in the 3% cash-back bonus categories and your Venture Rewards for all other purchases to earn 2 miles per dollar spent on them. With this duo, you can convert your cash back to Capital One miles and transfer them to any of Capital One’s 15-plus airline and hotel partners.

To learn more, check out our full reviews of the Capital One Savor Cash and Capital One Venture Rewards.

Learn more: Capital One Savor Cash Rewards
Learn more: Capital One Venture Rewards

Other ways to pair cards

Add a cobranded card for one of your card’s travel partners

If you already have a card that earns transferable rewards, pairing it with a card that earns rewards for one of its travel partners is a great option.

For instance, if you earn Chase Ultimate Rewards points with your Chase Sapphire Preferred Card, you might want to get the World of Hyatt Credit Card (see rates and fees) to access Hyatt-specific benefits like elite status and a free night each year.

Related: Best hotel cobranded cards

Diversify your rewards

While most combinations center around earning similar rewards, it’s also a good idea to earn different types of rewards. You could, for example, pair the Amex Gold with the Capital One Venture X Rewards Credit Card.

Asian young woman entering credit pin on the smartphone in the airport terminal — TWENTY47STUDIO/GETTY IMAGES

In this scenario, you would want to use your Amex Gold to earn bonus points on flights, dining at restaurants worldwide and groceries at U.S. supermarket purchases (up to $50,000 per calendar year for restaurants worldwide and up to $25,000 per calendar year for U.S. supermarkets, then 1 point per dollar spent thereafter) and your Venture X for your other purchases to earn 2 miles per dollar spent.

With this option, you can take advantage of both American Express and Capital One‘s transfer partners, giving you even more flexibility in your reward redemptions.

No annual fee

If you want to earn transferable rewards without paying an annual fee, pair the Capital One Savor Cash and the Capital One VentureOne Rewards Credit Card.

The VentureOne earns 1.25 miles per dollar spent on all purchases and allows you to turn Savor’s cash back into transferable Capital One miles.

Maximize bonus categories

If you’re OK with earning different types of rewards and want to make sure you’re maximizing all your purchases, you can set up your card portfolio with cards that earn bonus points in the categories you spend the most in.

Woman at a coffee shop — MOMO PRODUCTIONS/GETTY IMAGES

For example, you might opt for the Chase Sapphire Reserve to earn 3 points per dollar spent on your dining purchases; the Citi Strata Premier® Card (see rates and fees) to earn 3 points per dollar spent on your gas and electric vehicle charging stations and supermarket purchases; and the Capital One Venture Rewards Credit Card to earn 2 miles per dollar spent on all other purchases.

According to TPG’s April 2026 valuations, this combination would mean you’re getting an 3.7%-6.2% return on all your spending.

Set up your ideal structure

Of course, different card combinations work well for different goals. Identifying your credit card goals will help you decide which qualities to focus on when you choose your next card.

For instance, if you want to minimize your annual fees while earning travel rewards, your best card pairs may differ from those listed above.

TPG lead writer Katie Genter pairs her Ink Business Preferred with her Chase Freedom Unlimited, as it allows her to maximize her Chase Ultimate Rewards points while only paying one $95 annual fee.

Bottom line

The smartest credit card strategy often involves pairing cards that complement each other. Start by taking stock of what’s already in your wallet, then align your next card with your spending patterns and reward goals.

With the right combination, you’ll unlock even more value — and be well on your way to maximizing rewards for travel, everyday purchases and beyond.

For rates and fees of the Amex Platinum, click here.
For rates and fees of the Amex Gold, click here.

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Stacie Harris

Stacie Harris is a local resident and reporter of the Maple Grove area. Stacie reports on medicine and science for the Maple Grove Report.

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Data Science vs Business Analytics

1. What is Data Science?
2. What is Business Analytics?
3. Key Differences Between Data Science and Business Analytics
a.Basic Definition
b. Type of trends
c. Type of Data
d. Coding or Programming languages
e. Companies
4. Data Science vs Business Analytics
Roles and Responsibilities
Career path
Skills required
Type of Data
5.Conclusion

The popularity of Data Science has increased rapidly in the past few years and continues to increase with every passing data. As the organisations continue to create massive amounts of data, the implementation of Data Science becomes an obvious scenario.

If any company wishes to grow along with enhancing its user satisfaction, Data Science is something they need. Data Science uses modern techniques and tools to draw insights from that data which helps in making effective business decisions. It also uses several complicated Machine Learning algorithms to form predictive models.

Business Analytics is a practice used by companies to figure out what is happening in their business and how they can improve it. It helps in the overall decision making along with some future planning.

Since every company today is producing chunks of data, they need some data-oriented methods to draw insights from their past and present data to understand their loopholes which in turn helps them make some strategies keeping the current market trends in mind.

Now, when you know the basics of both Data Science and Business Analytics, it’s time to dive in deep and understand the main differences between the two popular terms.

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Key Differences Between Data Science and Business Analytics

There are several steps that are common in both like data gathering, data modelling, and drawing insights from that data. But, this is definitely not it, Data Science and Business Analytics are two big oceans that might meet somewhere, but are entirely different.

Let’s have a look at the differences between the two in elaboration.

Basic Definition

Data Science as the name suggests is the science of data, i.e. study of data using several Machine Learning algorithms, statistical tools, and other technological support. It is a combination of diverse fields like programming skills, mathematical principles, analytical thinking, and domain expertise to draw insights from huge amounts of data.

Business Analytics focuses on the business data and uses several analytical tools to draw insights from that data eventually scaling the business. It is a data-driven approach that focuses on historical data, identifying trends from there, checking out if there is any pattern and if there was a problem, what is the root cause of that problem.

Type of trends

Data Science focuses on all the trends and patterns leaving no page unturned to make an effective business model.Business Analytics revolves around the trends and patterns that reveal insights related to a particular business.

Type of Data

Data Science focuses on all types of data structured, semi-structured and unstructured data. To understand that structured data is highly refined and everything is just in front of your eyes, unstructured data is all complicated with no clarity on the type of data. So, Data Science uses several tools and techniques to work on different types of data. Business Analytics is concerned with organisational data. It uses several data analytics tools and other statistical principles to explore the organisational data and have an effective decision-making process.

Coding or Programming Languages

Data Science requires some rigorous algorithmic coding, statistical tools, and other analytical work to draw insights from tons of data. Languages like R and Python are widely used in several Machine Learning algorithms. Also, when unstructured data is concerned, knowing a programming language is a must. Apart from R and Python, you can also choose to learn C, C++, Perl and Java.

Business Analytics requires minimum coding as it is mostly focused on drawing insights using several statistical methods. Even if there is something advanced to be done, you can use advanced statistical methods as mostly the data is concerned with a single problem. So, business analytics tools like Tableau and Splunk are enough to draw insights from the organisational data.

Companies

Data Science is used in several big sectors today like e-commerce, machine learning, design and manufacturing, and marketing and finance. Data Science helps companies to understand how they can use their data effectively, whether it is about taking important business decisions or hiring more employees or even keeping a check on the workflow.

Business Analytics is used in industries like healthcare, marketing and finance, supply chain, and telecommunications. The biggest advantage of using business analytics is the reduction of risk as when the decisions are made using Business Analytics there are several factors covered like customer data, their preferences, market trends, the popularity of products etc, which may be missed otherwise.

Now, when you know the difference between Data Science and Business Analytics, let’s distinguish between a Data Scientist and a Business Analyst.

Data Scientist vs Business Analyst

Data Science is way bigger than Business Analytics and considers several factors that Business Analytics doesn’t even think of. While Business Analytics just focuses on business-related issues, Data Science even digs into the influence of factors like weather, customer preference, and several seasonal factors.

Let’s understand the differences between the two on a professional level, i.e. the differences between a Data Scientist vs. a Business Analyst.

Roles and Responsibilities:

Roles and Responsibilities of a Data Scientist include extracting and organising data. They draw meaningful insights from that data which could be structured or unstructured. To do all of it, they must have good knowledge of Machine Learning, Statistics, Probability, and other mathematical skills. Furthermore, they must have a firm grip on concepts like Python, R, Spark, Hadoop, and Tensor flow.

The roles and responsibilities of a Business Analyst include communicating with clients and providing them with business solutions. They must have great interpersonal and management skills to assist clients in designing and implementing relevant technical solutions. Along with all the assistance, they are always on their A-game in monitoring the overall business growth.

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Career path – The future

No matter what the sector is, be it healthcare, finance, management or transportation, the data needs to be taken care of and insights must be taken from that data for that industrial segment to grow. So, to make sure this happens, companies are looking for experts and no doubt Data Scientist is one of those job roles that are in most demand today and are one of the highest paying jobs in the world. The demand for Data Scientists is not going to reduce anytime soon considering the rapid production of granular data across the globe.

Business Analyst is one of those jobs that report a great level of work-life balance and job satisfaction. Again, it is one of those job roles that have a lot of openings in the market and one of the well-paid jobs too. Business Analysts are in great demand among organisations that are looking forward to scaling their businesses and improving their overall performance. The best part is the role of a Business Analyst is not limited to one designation, it changes from company to company. There are several roles that you can pursue if you have expertise in Business Analysis like Network Analyst, Project Manager, Data Analyst, and Business Consultant.

Skills required

Skills required to be a Data Scientist include:

Python – Data Science requires a firm hold of programming languages. When it comes to programming in Data Science, Python is one of the most widely used programming languages as it is easy to use and highly adaptable, even for people without a coding background.

Keras – Keras is used for artificial neural networks as they provide a python interface. Hence, they are used when it comes to experimentation with neural nets, that too at a great speed.

PyTorch – PyTorch is another deep learning framework extremely popular for its agility and compatibility with the Python framework. The framework simplifies the overall process to create an Artificial Neural Network (ANN).

Computer Vision – Computer Vision enables the Data Science systems to extract knowledge from images and videos to make necessary decisions.

Deep Learning – Deep Learning is something that makes the entire Data Science system more accurate as it enables the creation of extremely complex models.

Natural Language Processing – Natural Language Processing or NLP is something that is bridging the gap between Data Science and humans, by teaching computer systems how to read and interpret like humans.

Problem-solving – Problem-solving just doesn’t refer to the problem that is in front of you, being a Data Scientist you are responsible for solving problems that may be hidden.

Analytical Thinking – Data Scientists must have an eye for detail and analyse problems before actually starting to deal with them. It is important to examine the problem from all verticals and then reach an effective conclusion.

Skills required to be a Business Analyst include:

Programming skills – Programming Skills are not a must for a Business Analyst, but having some is always a plus. For example – knowledge of R and Python can help you in a quick and effective analysis of data.

Statistical analysis – Business Analysis requires a good knowledge of statistics and knowledge of different statistical methods to interpret real-world situations.

Business Intelligence tools – Business Intelligence or BI tools enable you to understand different trends and insights from business data, which is important to make impactful decisions.

Data mining – Data mining is one of the important skills of Business Analysis as it is about digging relevant information from chunks of data. So, companies use software to look for patterns and graphs in data and make relevant business decisions accordingly.

Analytical problem-solving – Business Analysts are about solving issues coming from customers or other stakeholders, so having the skill of analytically solving problems is a must.

Data visualisation – To make any important and accurate business decisions, the first and foremost step is to visualise or examine data chunks to understand market trends and loopholes.

Type of Data

Data Scientists work on both structured and unstructured data to fetch insights from huge chunks of data.

Business Analysts are just concerned about the structured data. They work on that data with several Business Intelligence tools to draw insights.

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Conclusion

By now, you would be well versed with everything you need to distinguish between the two most popular terms today – Data Science and Business Analytics. You began with learning the basics of the two and once you knew their basics you went on to differentiate between them.

While we were checking the differences between Data Science and Business Analytics, we checked several parameters to differentiate them and saw how they are different in the current scenario. While one is more technical and broad, the other one is comparatively less technical but a lot business-oriented and comparatively more specific.

You not only learned about the difference between the two huge concepts but also saw their differences on the professional level by finally distinguishing between a Data Scientist and a Business Analyst. In that segment you saw how one of them has to be proficient at coding and several statistical tools, after all, they operate on both structured and unstructured data, while the other one needs Business Intelligence tools to work on structured data and draw relevant business insights.

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