![\"Your](\"https:\/\/adamriemer.wpenginepowered.com\/wp-content\/uploads\/2026\/09\/Your-Best-Selling-Product-is-Not-Based-on-the-Number-of-Sales-scaled.jpg\")
<\/p>\n
The \u201cbest selling\u201d product or product category on an ecommerce site is not normally the one with the highest number of sales or largest dollar amount in sales.\u00a0 It could also change depending on your goals like moving inventory, increasing AOV, and improving profit per customer.<\/p>\n
If a product shows up in Google via SEO for a high volume query and with an intent to shop, that product or category going to sell better than everything else.\u00a0 When that ranking eventually goes away, the sales do too and then you find your actual best selling product.\u00a0 The same goes for a product getting a ton of Pinterest or PPC referrals from Merchant Center and datafeeds.<\/p>\n
A lower converting or priced product that gets reorders, has regular cross-sells added to cart, and builds customer loyalty is where you want to look as that is likely your best seller.\u00a0 It does not depend on a specific traffic source, but works across your audience as a whole.<\/p>\n
To find these in an ecommerce store, try looking at:<\/p>\n
- \n
- The number of sales and conversion rates from branded traffic coming in<\/li>\n
- Conversion rates from non-product specific traffic<\/li>\n
- Conversion rates for non-branded traffic<\/li>\n
- Repeat purchases and LTV for the product<\/li>\n<\/ul>\n
Here\u2019s a recent example of how we optimized the upsell tree in a client\u2019s checkout, then three ways you can use the above to find your best sellers and hopefully drive more conversions and revenue.<\/p>\n
A Real Recent Example With Conversion Rates and Expiration<\/h2>\n
The client sells a specific type of food and uses WooCommerce.\u00a0 They have FunnelKit installed in their checkout process which has a very easy-to-use logic tree and data display feature.<\/p>\n
- \n
- The logic section lets you define that if X is in the cart do not show the product, or if A and B are in it, then definitely prioritize ABC as the next product to feature.<\/li>\n
- The data section shows you the order of the upsells and the total conversions across all site traffic that reach them at checkout in a list.<\/li>\n<\/ul>\n
This client needs to move desserts faster than other upsells, so desserts were always the primary upsell.\u00a0 It turns out that desserts were not the highest converter compared to complementary proteins and some of the side dishes.\u00a0 But that didn\u2019t mean I should shift these top to the top as that could work against us.<\/p>\n
Unlike retail products that can be liquidated, perishables are a loss once they pass the expiration or sell by date.<\/p>\n
The food space is a bit unique as you have:<\/p>\n
- \n
- Product expiration<\/li>\n
- Perishables going out with unpredictable weather<\/li>\n
- Tariffs reducing margins substantially (this has always been the case historically)<\/li>\n<\/ul>\n
I shifted one of the side dishes to the second position as it was something we stock regularly, has a high conversion rate, and good margins.\u00a0 This put the dessert to the second upsell.\u00a0 After two weeks the side dish kept its strong conversion rate and there was no shift in the dessert\u2019s rate, so the client was now more profitable as there was more product in the cart and more money being made.<\/p>\n
Since dessert sales were not impacted, I looked site wide at the biggest protein upsell (think bacon, wagyu burgers, salmon filets, shrimp, jumbo crab meat, etc\u2026).\u00a0 This was already something people would add on based on the conversion rates, but not many had it already in cart because it isn\u2019t a heavily pushed feature on the website.\u00a0 So I moved a protein to the second position making dessert now the third.<\/p>\n
The protein in the second upsell position did get added but the conversion rate dropped a bit.\u00a0 The dessert was moved to position four and actually kept its conversion rate.\u00a0 The exposure rate declined a little bit as it was a few clicks in, but not enough to cause concern.\u00a0 This is natural with upsells that aren\u2019t forced click throughs.<\/p>\n
At this point total cart value was high and helped offset the expensive shipping costs, but we still need to move desserts.\u00a0 Since upsells weren\u2019t working as fast as we needed them to, we\u2019re running promotions via email and ads, and we\u2019re going to be trying \u201cfree dessert with XYZ\u201d types of packages.\u00a0 These tend to move the needle.\u00a0 If the client gives permission in the future I\u2019ll do a case study with numbers or examples in it.<\/p>\n
The result was an increased AOV and more profitability by simply knowing what our actual best sellers were in an upsell tree.\u00a0 Now ignore the upsell example and needing FunnelKit.\u00a0 Here\u2019s how to get your best sellers from your own shopping cart whether it is Shopify, WooCommerce, BigCommerce, or a custom built cart.<\/p>\n
Sales and Conversion Rates from Branded Traffic<\/h2>\n
Branded traffic converts high because the visitors know about your business and came ready to shop, or they\u2019re repeat buyers coming back.\u00a0 There is likely going to be a skew towards what they purchased before or know about you.\u00a0 For this part you want to isolate the data groups and then combine them later on.<\/p>\n
If you ran ads for a specific product line or category, or had something go viral on social media, that skews as the best seller because you promoted it and got traffic specific to it.\u00a0 If you had no ad budget or the above didn\u2019t happen, those sales will potentially tank.<\/p>\n
The first thing to do is to segment those sales out.\u00a0 For the items below, pull the total count and dollar amount for the first two, and the conversion rate for the third:<\/p>\n
- \n
- SKUs and product types added to cart from non-influenced traffic (traffic that does not have specific product intent).\n
- \n
- Use your tracking parameters like ad groups, keywords, etc\u2026 to find influenced traffic.<\/li>\n<\/ul>\n<\/li>\n
- How many returns you get from their products as this can make a top seller a lot less profitable than a third best seller.<\/li>\n
- The conversion rate on new products from your existing loyal base, and check whether that same base converts on new products when they arrive through branded search versus other channels.\n
- \n
- This help show whether it\u2019s the product is working across the audience or just brand trust carrying it to checkout.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
Having this lets you know what your current audience is interested in, and shows the products that convert in general without brand loyalty and external influences.\u00a0 These are products to feature in your emails to existing customers, as well as remarketing ads if they recently shopped for the complementary products but didn\u2019t buy them.<\/p>\n
Conversion Rates from Generic Traffic<\/h2>\n
Generic traffic could be someone asking ChatGPT for the best stores for apples, or someone looking on Google for bras, but not specifying the type, material, or style of bra.\u00a0 This is where they find the brands that sell the products and go to visit them.\u00a0 In both cases the person knows they have a specific purpose and use, but it isn\u2019t defined to a specific variety.<\/p>\n
The person shopping for apples could be looking for apples to bake with or to eat as a snack.\u00a0 If it is snacking apples and you have 100 visitors coming in from the word \u201capples\u201d, you can now find your best selling snacking apple as there\u2019s no modifier other than snacking, it is just apples in general.<\/p>\n
If you ranked in Google and got LLM traffic for \u201cfuji apples\u201d and that was mixed in, this skews the data and fujis would win, when in reality it was the honeycrisp or cosmic apple that are actually the best seller.\u00a0 If you focus everything on fuji, you could be less profitable because it is not your best seller, you just included product specific traffic in the mix.<\/p>\n
The person searching for bras may want lift and support, so as they reach your page they\u2019ll find shelf\/balconette, push up, and side support.\u00a0 In the survey you do after purchase you\u2019ll learn who came in specifically for this style, and then you can cross reference which of these three styles won out over the others.\u00a0 The non-influenced traffic (i.e. didn\u2019t type balconette bra in specifically) is the one that shows your best selling bras for lift and support.<\/p>\n
This information lets you know what to place as a higher priority in your product mix, in your shopping ads across online platforms, and to feature in email reminders to replace your undergarments.\u00a0 If most of the traffic was specific to push up, that is why push ups are your best seller, but that doesn\u2019t mean they\u2019re right for the general audience.<\/p>\n
Repeat Purchases and LTV<\/h2>\n
The last way to know what your best sellers are may not be reliant on the number of orders or AOV (average order value) at all.\u00a0 It could be the lifetime value and total number of purchases from the customer.\u00a0 Especially if the return and replace rates are lower than top converting products.<\/p>\n
You may have a product category that converts lower than others and has a lower AOV.\u00a0 But these customers stay for five years or purchase 8 times over their lifetime as your customer.\u00a0 The top converting option may have subscribers for 3 years, or that only place 5 orders in the lifetime.\u00a0 While we\u2019d be paying attention to the higher converting and larger order numbers, they may not be as profitable and this is why they\u2019re not necessarily the best sellers.<\/p>\n
If the first product has an AOV of $100 and 5 years, that is $500 per customer in gross.\u00a0 The second product has an AOV of $120 and the customer stays for 2 and 1\/2 years.\u00a0 This results in $300 gross.\u00a0 The AOV is lower on product 1 but you make an extra $200 in gross profit.\u00a0 And if your company gets refer a friend traffic, you have an additional 2 and 1\/2 years of high-value referrals coming in as they\u2019re customers for a longer period of time.<\/p>\n
Best selling products are not always the ones that have the highest number of orders or the largest AOVs, and top selling products don\u2019t always mean they\u2019re the most profitable.\u00a0 Top sellers are the ones people gravitate to when they know they need something from a category of products with a specific idea in mind, and then the majority choose one or two options.\u00a0 From there it is a matter of how long they stay a customer and how many repeat orders they make.<\/p>\n
By having clean data sets you can discover your best sellers and most profitable products so you know where to invest marketing budget to grow your company for long term success.\u00a0 These are things we do with our clients, especially in merchandising, upsell and cross sell paths, and I hope this helps you do the same.<\/p>\n<\/p><\/div>\n\n","protected":false},"excerpt":{"rendered":"
The \u201cbest selling\u201d product or product category on an ecommerce site is not normally the one with the highest number of sales or largest dollar amount in sales.\u00a0 It could also change depending on your goals like moving inventory, increasing AOV, and improving profit per customer. If a product shows up in Google via SEO […]<\/p>\n","protected":false},"author":1,"featured_media":7061183,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11761],"tags":[3528,4755,1463,1329,7846],"dealstore":[],"offerexpiration":[],"class_list":["post-7061182","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-affiliate-marketing","tag-based","tag-number","tag-product","tag-sales","tag-selling"],"yoast_head":"\n
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- This help show whether it\u2019s the product is working across the audience or just brand trust carrying it to checkout.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
- SKUs and product types added to cart from non-influenced traffic (traffic that does not have specific product intent).\n