Increase Your BigCommerce Sales with Proven A/B Testing Methods

In the cutthroat e-commerce market, even little changes to your BigCommerce store could make a big difference in sales. A/B testing is a great way to find and apply these improvements so that your store not only looks great but also maximizes conversion possibilities. This blog will guide you through doable A/B testing techniques meant to boost your BigCommerce sales.

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Why A/B Testing Matters for BigCommerce Stores

- Data-Driven Improvements: A/B testing lets you make judgments grounded in real user behaviour instead of depending on conjecture or intuition.

- Enhanced User Experience: Testing many components of your site will help you to find what appeals most to your audience, thereby improving the buying experience.

- Higher Conversion Rates: Correct identification and application of little modifications can greatly increase sales and general income.

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Proven A/B Testing Methods for BigCommerce

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1. Experiment with Product Titles and Descriptions

- Why: Often the first things a prospective buyer views are your product titles and descriptions. They must be interesting enough to inspire more investigation.

- What to Test: Change the length, style, and language of your product names. For descriptions, try several styles like bullet points instead of paragraphs and vary in degrees of detail.

For instance, the "Luxury Leather Wallet" contrasts with the "Premium Leather Wallet with RFID Protection."

Tip: Include relevant keywords to improve both search visibility and appeal.

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2. Optimize Call-to-Action (CTA) Buttons

- Why: CTA buttons lead your guests to a purchase. Conversion rates can be influenced by their design, location, and language.

- What to Test: Test several button colours, sizes, placements on the page, and even the text choice. Here, little adjustments can have a significant impact.

For instance, "Add to Cart" against "Shop Now" against "Get Yours Today."

Tip: Ensure your CTAs stand out visually but remain consistent with your brand’s overall aesthetic.

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3. Tweak Pricing Presentation

- Why: Purchase decisions heavily rely on pricing; thus, how you show prices will affect perception and sales.

- What to Test: Experiment with pricing strategies like showing prices with and without discounts or testing several pricing points.

For instance, "$19.99" vs "$20" against "$25 with a 20% discount."

Tip: Consider testing how price presentation affects customer segments, such as first-time visitors versus returning customers.

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4. Improve Product Images and Videos

- Why: High-quality visuals help customers better understand what they’re buying, increasing their confidence and likelihood to purchase.

- What to Test: Test different image styles, angles, and the inclusion of videos. Compare the impact of static images against interactive elements like 360-degree views.

- Example: A standard product photo vs. a lifestyle image showing the product in use.

Tip: If using videos, test different lengths and formats to see what keeps users engaged the longest.

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5. Simplify Your Checkout Process

- Why: A complicated or lengthy checkout process can lead to cart abandonment, costing you sales.

- What to Test: Experiment with single-page versus multi-step checkouts, the number of required fields, and the option for guest checkout.

- Example: A streamlined, one-page checkout vs. a traditional multi-step process.

Tip: Monitor how each variation impacts your cart abandonment rates and overall conversion.

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6. Refine Navigation and Page Layout

- Why: Easy navigation helps users find what they need quickly, reducing frustration and leading to higher sales.

- What to Test: Test different layouts for your product, category, and homepage. Consider experimenting with navigation menus and filter options.

- Example: A grid layout for product listings vs. a list layout.

Tip: Pay attention to mobile users, ensuring that your layout tests also optimise the experience on smaller screens.

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7. Leverage Social Proof

- Why: Customer reviews and ratings can build trust and influence purchasing decisions.

- What to Test: Try different placements for reviews, such as below the product description or in a separate tab. Test the inclusion of star ratings and the impact of testimonial design.

- Example: Customer reviews at the bottom of the page vs. integrated within the product details.

Tip: Highlight the most relevant and positive reviews, but ensure authenticity by displaying a mix of feedback.

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How to Implement A/B Testing in BigCommerce

‍1. Define Clear Goals

Before starting any test, establish what you aim to achieve. Whether it's increasing the average order value or reducing bounce rates, having a clear goal will help guide your testing efforts.

‍2. Choose the Right Tools

Several A/B testing tools are compatible with BigCommerce, including Customfit.ai, Google Optimize, Optimizely, and VWO. These tools allow you to create, manage, and analyse your tests.

‍3. Formulate Hypotheses

Create a hypothesis about what will improve your site's performance before you start running tests. For example, "I believe red CTA buttons will increase click-through rates."

‍4. Run the Test

Ensure that you split your traffic between the different variations and allow the test to run for a sufficient time.

‍5. Analyze the Results

Once the test is finished, use statistical analysis to identify which variation performed best. Look for substantial improvements and examine how they relate to your initial aims.

‍6. Implement the Winning Variation

If the results are conclusive, roll out the winning variation across your website. Continue to watch its performance and consider conducting further tests to improve your store.

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What is A/B testing in BigCommerce, and how can it help improve sales?

A/B testing, commonly known as split testing, compares two alternative versions of a webpage to determine which performs better. BigCommerce defines this as testing product pages, checkout processes, or calls to action (CTAs). One group of visitors will see Version A, while another will see Version B. The idea is to see how each version affects conversions (sales, sign-ups, and other measurable activities). This strategy assists store owners in determining whether design or content modifications result in higher sales and fewer abandoned carts. For example, a more enticing CTA may increase conversions by making customers more inclined to complete a purchase.

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How should my BigCommerce store be configured for A/B testing?

To initiate A/B testing on BigCommerce, take the following actions:

1. Select an A/B testing-supporting tool, such as Customfit.ai, Convert, Optimizely, or Google Optimise.
2. Connect the instrument to your BigCommerce store.
3. Select a specific element (e.g., product descriptions, button colour, or page layout) that you wish to test.
4. Make two versions of the testing tool: Version A and Version B.
5. Describe the audience division. Visitors will be assigned to either version at random by the tool.
6. Make sure to run the test long enough to collect enough data for statistical significance.
7. Examine the outcomes to determine which version does better about important indicators such as average order value or conversion rate.

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Which A/B testing procedures work best in BigCommerce?

Among the best methods for A/B testing in BigCommerce are:

1. Test each component separately: Steer clear of trying too many variables in one test to accurately determine what is working. Concentrate on a single alteration, like the colour of the button or the headline.
2. Run the tests for a long enough time: Make sure the test runs long enough to collect adequate information. Allowing the test to run for at least two weeks is a good idea to account for variations in weekend and weekday purchasing habits.
3. Employ a sufficiently big sample size: Your test results won't be trustworthy if the test audience is too tiny. Your results will be more reliable the more visitors you test with.
4. Pay attention to important conversion points: Test features like "Add to Cart" buttons, checkout forms, or product photos that have an immediate effect on your sales.
5. Repeat depending on outcomes: Apply what you've learned and keep fine-tuning elements based on data after every test.

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How can my BigCommerce store's conversion rates be increased by personalisation?

Increasing conversions and improving the customer experience can be accomplished with the help of personalisation. You may create a personalised shopping experience for each visitor by customizing marketing campaigns, product recommendations, and content to suit their tastes. 

For instance:

1. To suggest relevant products, use past purchasing behaviour.
2. Display location-specific shipping alternatives or incentives.
3. Offer customised rewards or discounts to loyal clients. By providing a more relevant purchasing experience, this individualised strategy fosters recurring business, promotes client loyalty, and dramatically boosts conversion rates.

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Which resources are available on BigCommerce for A/B testing?

BigCommerce is compatible with numerous external A/B testing solutions, such as:

CustomFit.ai: A flexible platform called CustomFit.ai was created especially to maximise conversion rates by providing users with individualised experiences. Whether you are in charge of an eCommerce store or another kind of website, this tool aids in the creation of customised content and user journeys based on the interests and behaviours of each visitor, increasing engagement and conversion.

Google Optimize: It is a user-friendly, free tool for creating A/B tests. It works well with Google Analytics integration.

Optimizely: A potent A/B testing tool with cutting-edge capabilities including multivariate testing and personalization.

Convert: Well-liked for its user-friendly UI and extensive BigCommerce integration, Convert is an A/B testing solution. With the help of these tools, you can make data-driven decisions by tracking visitor activity, creating multiple versions of your store's pages, and analysing the outcomes.

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How can I leverage BigCommerce's customer data for personalisation?

Effectively personalizing the buying experience can be achieved by utilizing a variety of consumer data categories, including:

1. History of browsing: Display products according to what users have looked at or typed in.
2. Purchase history: Make customised recommendations depending on what you've already bought. For example, you could suggest the newest models or accessories to a consumer who often purchases tech devices.
3. Geolocation: Offer promotions based on a user's location, such as free delivery in particular areas.
4. Behavioural data: You can provide incentives like time-limited discounts or free trials if a consumer tends to browse but not buy. You can increase engagement and conversions by using this data to tailor experiences for your customers and help them feel understood.

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Can I improve my BigCommerce product pages using A/B testing?

Indeed, improving product pages is a particularly good use case for A/B testing. To find out what encourages the most conversions, you can test out different aspects of your product pages:

Descriptions of products: Experiment with various lengths, tones, and formatting designs.

Images: To determine which kind generates more purchases, test 360-degree panoramas, high-quality images, and customer-submitted pictures.

Buttons with a call to action (CTA): Try varying the text ("Add to Cart" vs. "Buy Now") or the colour to see which attracts the most clicks.

Format for product pricing: Try several layouts, such as emphasising discounts or showing alternatives for monthly payments, to see which encourages more purchases. Customer decision-making heavily relies on product pages, therefore improving them can directly and favourably affect your sales.

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How can I evaluate A/B testing outcomes in BigCommerce?

Determining what resonates with your audience requires analysing the outcomes of A/B tests. Compare each version's performance using metrics such as these after the test.

1. Which version resulted in more sales in terms of conversion rate?
2. Average order value (AOV): Did a particular version entice buyers to purchase more expensive or larger-sized goods?
3. Bounce rate: How many people left the page without doing anything?
4. Metrics of engagement: amount of time spent on the page, clicks on particular parts, etc. Track these numbers and determine which version was more successful by using a tool such as Google Analytics or the reporting dashboard of your A/B testing solution.

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Which critical metrics should be monitored when conducting A/B testing on BigCommerce?

It's critical to concentrate on key performance indicators (KPIs) that have a direct impact on your store's success while conducting A/B testing. Among the crucial metrics to monitor are:

1. Conversion rate: This indicates the proportion of visitors who become clients. It's the most significant indicator of how well A/B testing is working.
2. Bounce rate: A page that keeps visitors on it longer has a lower bounce rate.
3. How many individuals click on a call to action (CTA) or other important elements is tracked using the click-through rate (CTR).
4. Average order value (AOV): Check to see if your test contributes to a higher average consumer purchase price.

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How can I use A/B testing to enhance my BigCommerce email marketing strategy?

A/B testing can be used for email campaigns by testing the following:

1. Subject headings: Try varying the subject line's phrasing, length, or tone to see which encourages readers to open the email.
2. Email layouts: To determine which design generates more clicks and conversions, experiment with alternative layouts, graphics, and CTA buttons.
3. Send times: To increase open rates, determine the ideal time of day to send emails. You may optimise your email approach for greater engagement and conversions, which will help bring customers back to your store, by testing and evaluating the outcomes.

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How can I customise the BigCommerce shopping experience to increase recurring sales?

Utilise consumer information to customise the purchasing experience to promote recurring purchases:

1. Product recommendations based on previous purchases: Make suggestions for related products or updated iterations of things they've already purchased.
2. Send customised email offers: Give them early access to sales or special discounts depending on their purchasing patterns.
3. Personalise the homepage or recommended products: Show each consumer relevant items according to their browsing history and preferences. Customisation gives clients a sense of worth, which increases their loyalty and motivates them to visit your business again.

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What typical errors should be avoided while using BigCommerce for A/B testing?

Among the typical errors to steer clear of are:

1. Doing too much testing at once can make it challenging to determine which modification produced better outcomes.
2. Too little time spent on tests: If your site receives little traffic, results from quick tests might not be trustworthy. Extend the test sufficiently to obtain statistically significant findings.
3. Lack of defined objectives: A clear objective for every test should be established, such as lowering cart abandonment or raising the conversion rate.
4. Neglecting outside influences: Be mindful of any seasonal patterns, sales, or traffic variations that could have an impact on the outcomes of your test.

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Conclusion

For any BigCommerce store trying to boost sales and enhance customer experience, A/B testing is a vital tool. Through methodical testing and optimisation of various elements of your website, you can make data-driven decisions that result in noticeable enhancements to the operation of your store. Always remember to use appropriate techniques, set clear goals at the outset, and be willing to refine your results as you go. You'll be well on your way to increasing your BigCommerce store's success and conversion rates with these tactics in place.

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Are you ready to increase your store's conversion rates with effective A/B testing? Download the CustomFit Shopify A/B Testing App today and begin optimising your business to provide personalised experiences that increase sales.

Click the button below to get started right now: Download the CustomFit A/B Testing App for Shopify

Start testing smarter, not harder, and see your conversion rates skyrocket!