Easy Six Steps To Boost Top Products & Make Winners Bigger Winners
1. Pull data from any web analytics platform (although Google Analytics is a little tougher to get this data). You'll want to start with a list of most viewed (not ordered or revenue) items in last 90-180 days and with those products you'll need to know # of times added to the cart (per item), # of times removed from the cart (per item), # of units sold and # of unique purchases/orders. Pull this down to Excel and average out the top 80% of revenue items. Average all 3 metrics (% added to cart, % remove from cart and % order).
2. Highlight in yellow all metrics that fall below the benchmark average. Highlight in gree all metrics that fall 10% above the benchmark average.
3. Here are the likely causes for each factor that you will to focus on a resolve.
4. % Added to Cart - if this is below benchmark average, you likely have issues with 1 of the following - the image, the content or the price. The most likely are image and price. Check competition for image and price comparisons and test either one or the other. If you test both, you'll need to know you're working towards and aggregate improvement knowing that you are improving the image and lowering the price so the risks are low to negatively impact this metric.
5. % Removed from Cart - It's very likely a cause of A. Shipping costs were too high, B. Found another item, C. Received new information like backordered or minimum quantities or something, D. Promo code didn't work for item. Check all of these areas against your competitors and adjust. If you improve with low risk (lowering shipping or taking barriers away), just test to be sure you're keeping gross margin $ in line.
6. % of units sold and orders. If either of these are down, it's a likely cause that someone found the item somewhere else or just decided not to buy. If this unit is low in conjunction with % added, then you've made changes that could improve this metric. If this metric is low in conjunction with % removed, then you've again made changes. However if this is metric is low while the other two metrics are average or above (in green), then you may very well have an issue in your checkout and it's not necessarily with this item (although it could be if your promo code entry is in checkout). You'll need to analyze your checkout pages one by one to find issues and correct with A/B testing unless they are fixing errors.
As always, I'm available at heartlandgirl21 on yahoo mail. Have a great week.
1. Pull data from any web analytics platform (although Google Analytics is a little tougher to get this data). You'll want to start with a list of most viewed (not ordered or revenue) items in last 90-180 days and with those products you'll need to know # of times added to the cart (per item), # of times removed from the cart (per item), # of units sold and # of unique purchases/orders. Pull this down to Excel and average out the top 80% of revenue items. Average all 3 metrics (% added to cart, % remove from cart and % order).
2. Highlight in yellow all metrics that fall below the benchmark average. Highlight in gree all metrics that fall 10% above the benchmark average.
3. Here are the likely causes for each factor that you will to focus on a resolve.
4. % Added to Cart - if this is below benchmark average, you likely have issues with 1 of the following - the image, the content or the price. The most likely are image and price. Check competition for image and price comparisons and test either one or the other. If you test both, you'll need to know you're working towards and aggregate improvement knowing that you are improving the image and lowering the price so the risks are low to negatively impact this metric.
5. % Removed from Cart - It's very likely a cause of A. Shipping costs were too high, B. Found another item, C. Received new information like backordered or minimum quantities or something, D. Promo code didn't work for item. Check all of these areas against your competitors and adjust. If you improve with low risk (lowering shipping or taking barriers away), just test to be sure you're keeping gross margin $ in line.
6. % of units sold and orders. If either of these are down, it's a likely cause that someone found the item somewhere else or just decided not to buy. If this unit is low in conjunction with % added, then you've made changes that could improve this metric. If this metric is low in conjunction with % removed, then you've again made changes. However if this is metric is low while the other two metrics are average or above (in green), then you may very well have an issue in your checkout and it's not necessarily with this item (although it could be if your promo code entry is in checkout). You'll need to analyze your checkout pages one by one to find issues and correct with A/B testing unless they are fixing errors.
As always, I'm available at heartlandgirl21 on yahoo mail. Have a great week.
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