Thanks to advances in commerce-related applications of machine learning and AI there is a significant opportunity to modernize the parts and accessories shopping experience. In this post, we’ll explore trends and applications of ML/AI to optimize the experience for the parts and accessories shopper across their journey from acquisition to engagement through retention.
Just over a decade ago, supporting accurate search results for parts and accessories within fitment was labor-intensive and very difficult. Now, most online auto parts retailers and marketplaces support fitment-based results and filters, however, the results are generally the same for each shopper. No two shoppers are identical — even if they are shopping for parts on the same vehicle. Key differences, just to name a few, including how the vehicle is operated, under what conditions it is operated, where, when, and what has already been done to the vehicle, etc. When layering in buyer intent data based on real-time actions, ML/AI tools can use all of these variables to personalize buyer experiences.
Automotive part shoppers typically fall into the following types:
- Reactive: repairing their vehicle
- Routine: maintaining their vehicle
- Aspirational: enhancing their vehicle
- Professional: working on vehicles of others
Addressing each shopper individually is key. Showing relevant products accurately based on fitment intent can be determined through acquisition details and onsite engagement: Acquisition / visit details: What brought them to your site and where did they land? Did the buyer come through organic/paid search, email, promotional, social campaigns, or was it direct traffic? When it comes to personalizing onsite search, how they land on your site gives away a significant amount of information about the buyer’s intent. Providing an instantly relevant experience is key for these shoppers. Building a relevant instantaneous experience would include: Dedicated individualized landing pages for each combination of part type and vehicle (make/model/year + type or category at a minimum) help both with the activation of search and campaign traffic while also providing additional context. These pages should contextually adapt to the shoppers' region, season/climate, trends, and historical data if available. In the CarID example below a dedicated landing page for the make + part-type can also drive more engagement incorporating some collaborative and contextual data such as ranking brakes most likely purchased by shoppers in a similar context (region, season, channel, etc).
Onsite engagement: Extract intent from onsite engagement touchpoints.
- What did they do on your site?
- Where did they navigate?
- What did they search and did they use specific filters?
- What did they click on?
Typical journey of a parts shopper
Let’s walk through the typical journey of a parts shopper. In these examples, we’ll be searching for “2008 honda fit front suspension.”
While searching on Google, parts shoppers receive basic experiences —not tailored to the automotive parts industry, nor a specific consumer. The results and experience is generally going to be the same for every shopper.
Amazon takes this a bit further with a specific automotive parts store supporting the concept of garage/fitment. However, the experience still does not factor in personal attributes.
Ebay’s “Shop by Diagram” takes a different approach by providing the shopper with a visual schematic of the specific vehicle to identify the correct part.
Automotive parts e-commerce sites
Going beyond marketplaces where auto parts is a category to dedicated automotive parts sites, we find more depth in the experience such as additional filters, categories and type-specific results aligned with what a part shopper requires to help with their selection vs. the generic experience of the marketplaces.
Category-specific result fields (dynamic results) provide an additional level of detail a shopper needs to make their selections.
As many shoppers will arrive via organic or paid search, a vehicle fitment + part category landing experience reduces the number of steps the shopper requires to their purchase. This also helps with SEO when included as part of your site navigation:
Finally, there are category-specific sites that provide even an additional layer of depth specific to their category of focus such as staggered fitment in tires.
Whether they are working on simple DIY vehicle maintenance or more complex projects, retrieving compatible parts with accuracy is only half the battle.
Shopper research also includes symptoms the part solves for, the category and function of the part, the part type, brand, OEM/aftermarket preferences, or part product number itself. The way in which the vehicle is used, where, and under which conditions are also important factors often neglected in fitment-based results. Shopping replacement parts can be complex due to size, shape, material, cross applications, etc.
Some buyers will be hesitant to purchase replacement parts online due to their level of confidence in receiving the correct part of their application without the help of an expert. An individualization platform eliminates this hesitation by not only presenting compatible parts but takes into account all factors to present the precise parts based on the shopper’s predicted needs and intent.
Create a seamless buyer experience—before your competitors do
Until now, auto commerce sites didn’t have the ability to create the kind of 1:1 individualized buying journey in the same way other online retailers do. Auto parts retailers’ complex fitment product offerings present a unique challenge to technologies that aim to simplify online buying and predict the buyer’s needs. Most legacy search and recommendation systems return compatible product results based on fitment, though not specific to the shopper's specific affinities such as use, materials, activity, brand, warranty, country of origin, etc. It is rare for an AI system to be able to do 1:1 individualization. It is even rarer for a system that can do 1:1 individualization and keep track of a user's affinities and handle large scale hard filters on year/make/model. To be able to do so requires an immense amount of processing capabilities, efficient backend algorithms, clean and easy to understand front end UI, and the latest backend architectures. Sitecore Discover’s AI-based Commerce Engagement Platform is just that. It optimizes end-to-end buying experiences for auto parts buyers through its robust fitment capabilities. Here is our checklist for turning your site from a catalog of confusion to the most valued assistant in your buyer's garage:
1. Organize and enrich your data
ACES (Aftermarket Catalog Exchange Standard) and PIES (Product Information Standard) are the top data organization standards for auto parts products and retailers. You can further enrich this data automatically with ML-based semantic and visual tagging, as well as crawling. Clickstreams provide additional insight on behavioral interaction with the product such as the optimal conversion path for a product. Historical transactions provide additional insight such as seasonality and contextual trends surrounding a product. In addition, incorporating data from multiple sources such as store data, social media, and other third-party sources to improve the thoroughness of your content, leading to higher engagement. With the right engagement platform, you can create individualized buying experiences using all of these data sources, which drives additional revenue.
2. Optimize your SEO exposure and site search experiences
Most shoppers start on google with a long-tail keyword which includes variations of fitment and product attributes/keywords. Optimizing your site with dynamic landing pages for long-tail keywords drives organic traffic. These dynamic fitment landing pages give merchants the opportunity to automatically create vehicle-specific experiences for individual buyers. Now you’ve got the buyer onto your site, a fitment-based site search is necessary. The complexity of the products sold in the automotive aftermarket industry demands robust site search capabilities. Your site should be prepared for shoppers to search by a range of terms including:
- Part type
- Engine type
- Part function
- Part symptoms
- Part use and application
- Part / manufacturer / competitor number
That’s quite a tall order, which is why AI and ML technologies are needed to ensure the search process is fast enough for today’s buyers. Another important consideration is to enable your site with a preview search interface. Preview search can predict the intent of your buyers from their very first click in the search bar, making helpful suggestions for products, categories, and brands that might best fit their needs. The image below shows what a buyer might see after typing just two characters. Essentially, this means that the buyer is shown suggestions as fast as their brain can perceive them. You should also use a buyers’ previous intents. For example, if a shopper looked for a replacement part for a 2016 Mazda CX5 Grand Touring SUV on one visit, it would preview parts for that make and model in subsequent searches based on that affinity — until a new intent is discovered. When personalizing the onsite search experience, seasonality is important to take into account. A person who likes racing will search for a certain type of tire during a defined season. The same person may be looking for snow tires for their family vehicle in October or November. This is something your site will “know” about them.
In addition to an agile preview and site search, you should ensure that your site has a filtered full-page search. Crucial facets are:
- Individualized results
- Fitment filters
- Universal fit or cross-fitment
- Facets relevant to fitment
- Faceted URLs
3. Let your shoppers explore by exact vehicle
Generate cascading filters that enable your shoppers to tell you exactly what vehicle they are shopping for. These filters:
- Only show fitments that have products or inventory
- Do not require ACES or PIES
- Can be explored by the buyer in any sequence
- Can accommodate additional fitment parameters
This information will take buyers straight to the vehicle dynamic landing page & product listing pages (PLP) categories they need. The machine/vehicle landing pages themselves are powerful customer acquisition and engagement tools. Your product detail pages should capture each buyer’s attention in exactly the way they would want, intuitively presenting the most relevant information and recommendations to them so you can effectively sway their interest—and their likelihood to click “add to cart.” Dynamically created fitment pages create a personalized page experience, so shoppers get targeted recommendations for their specific vehicle, including:
- Products within a fitment context
- Substitutions and replacements
- Cross-fitment and universal fit
These will also trigger content pushes such as banners, editorials, videos, and blogs to engage the shopper more deeply.
4. Offer fitment compatible recommendations
Recommendations must honor the fitment and context to be relevant. They offer an important opportunity to up-sell, cross-sell, and next-sell which drives additional revenue. Individualized recommendations take into account, not just the customer's fitment requirements or garage, but also their context and behavior. AI enables you to incorporate the behaviors of all shoppers past and present to drive the most relevant recommendations without any manual intervention.
Individualized collaborative recommendations include:
- Co-view/bought / ultimately bought, others like you bought honoring fitment
- Trending/top purchased for a given fitment, within the category
- Based on context, use, or application
- Recommendations based on cart contents and order history
- Replenishment based on fitment specific maintenance schedules
With Sitecore Discover’s Commerce Engagement Platform, you can choose, build, and test recommendation “recipes” to optimize revenue.
5. Allow buyers to create a custom garage
My garage, my machine, my ride—when the buyer shares this information, your site needs to listen and remember it. Give buyers the ability to create a “custom garage” which can be managed by your individualization platform. Using information from your customer profiles and CRM, the custom garage saves buyers time, ensuring that the next time they need something for their vehicle, they will get relevant and helpful suggestions from your site—instantly.
6. Reduce “speed bumps” in the purchase path
Across the buyer experience, you want as few steps as possible for a buyer to find what they need. Engagement and individualization platforms built for fitment enable all touchpoints to interact with each other based on the fitment and application of the products the buyer intends to buy. Your engagement platform should capture each individual visitor’s shopping behavior—extrapolating it from their site visits, purchases, clicks, and even their photos—and convert that behavior into a detailed understanding of what they want.
If what your buyer needs is a BOPIS option, you need to ensure they only see products available at their preferred location, incorporating real-time inventory, fulfillment, and pricing data.
With this deep understanding of your buyers’ preferences, it is possible to give them a smooth ride through search, recommendations, category/landing pages, email, and even in-store purchases so that more of your products cruise straight into their carts.
Email shouldn’t be forgotten. Incorporating individualized suggestions and content within the email, based on your garage or specific vehicles, significantly improves email open and click-through rates. Email landing pages continue the experience and individualization across channels, further driving higher engagement and conversion.
7. Leverage fitment analytics insights across channels
Finally, your 1:1 individualization solution should give you easy-to-access, in-depth analytics that will show you exactly who your audience is, and on which channels you can reach them. Fitment analytics will provide detailed information about sales for each year/make/model, and search, category, and product analytics will help you to understand how shoppers are interacting with your site across all touchpoints. You can also gain insight into when to replenish stock since AI can learn maintenance schedules based on aggregate purchasing behavior by vehicle.
Not only will your loyal customers be impressed with how seamless your site is, but they will also be astounded by the responsiveness of your staff. Through email, you can offer them service reminders based on published manufacturers’ schedules for their vehicle and let them know about recalls and promotions. Data-gathering capabilities are also extremely valuable for call-center representatives seeking to resolve issues quickly; they will know all about your buyers and their vehicles as soon as the calls come in. Your platform should also be mobile-friendly (which is helpful both for individual shoppers and floor mechanics) and provide connectivity with in-store kiosks and tablets.
With the auto parts aftermarket e-commerce industry burgeoning, not investing in individualization presents a serious opportunity cost. The time is now to implement a cost-effective individualization solution—before your competitors get one.
The time is now
With Sitecore Discover Commerce Engagement Platform, you can optimize end-to-end buying experiences for auto parts buyers through its robust fitment capabilities. Now is the time to create a seamless buyer experience before your competitors do.