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Taco Clout

Optimizing Search

Taco Clout is a full service, one stop shop, off-road parts and accessories store for your Toyota Tacoma, 4Runner, and Tundra. We offer a wide range of products from grilles, wheels & tires, lift kits, bumpers, and much more.

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Background

Toyota Tacoma owners, and I'm sure others, frequently search for specific parts based on their vehicle's year or generation. However, our research indicated that users faced challenges when searching by year due to the varying compatibility of parts across different model years & trims.

Objective

To determine whether customers prefer searching for Toyota Tacoma parts by year or by generation, and to improve the user experience accordingly.

Research Methodology

  • 1. User Interviews
    Conducted interviews with Toyota Tacoma owners to understand their preferences and pain points when searching for parts.
  • 2. Data Analysis
    Analyzed website traffic and user behavior to identify patterns in search queries and user preferences.
  • 3. A/B Testing
    Created two versions of the parts search interface: A (Parts search by year), B (Parts search by generation)
  • 4. Metrics Used
    I used Conversion Rate and Time on Page as my 2 main goal metrics for this test.
  • 5. Search Query Analysis
    Analyzed the most common search queries and user interactions.
screen shots of the 2 variations of tests I ran on Taco Clout

The results were pretty on par with what I was assuming based on how customers chatted in forums online about their trucks.

inital results from A/B tests

Conversion Results

Conversion Rate

πŸ‘‡ Version A (Search by Year): .36%

πŸ‘† Version B (Search by Generation): .44%, up πŸ‘† 22%

Time on Page Results

Time on Page

πŸ˜’ Version A: 3 minutes (spent more time looking for a product they wanted than browsing. I verified this through Microsoft Clarity app to watch real time user interactions on the website)

πŸ˜€ Version B: 1.5 minutes (users found what they wanted a lot faster, which also boosted add to cart rates)

Conclusion

Based on the A/B testing results and user feedback, it was evident that customers preferred searching for Toyota Tacoma parts by generation rather than by year. My assumption is that the use of generation terminology is more aligned with the language used in niche off-road modification forums and better reflects the compatibility of parts across different model years.

For example, in the Toyota Tacoma, years 2016 to 2023 look exactly the same. Nothing about the Toyota Tacoma, in 7 years, had changed. People referred to them as the β€œ3rd Gen Tacoma” or β€œ3rd Generation Tacoma.” This particular test was followed up by a subset of A/B tests, to test β€œGeneration” vs. β€œGen”.

Recommendations

Implement Parts Search by Generation: Update the website's parts search interface to allow users to search for parts by generation.
Improve User Education: Provide educational resources to help users understand the concept of searching for parts by generation and its benefits.

Future Considerations

Continuously monitor user feedback and behavior to further optimize the parts search experience.

Explore additional features such as predictive search and personalized recommendations to enhance the user experience further.