Updated: Mar 2
Note: We have updated this popular post with even more in-depth information and perspective as on March 1st, 2020.
Today, there are as many Amazon PPC strategies floating around, as there are gurus, consultants and PPC tools. While everyone is entitled to their opinion and we trust that's based on experience (data), for someone who is just trying to catch their breath from the constant barrage of Amazon PPC updates coming at them, all these theories can cause much confusion and misdirection.
In this post we present 5 highly contested approaches that are practiced and preached by gurus and tool vendors. We decided to lay it all out for you guys in as neutral a way as possible, for you to pick what makes the most sense to you. Read the description, the theory and the counter arguments and then form your own opinion.
Ok, let's jump in..
1. Add Negative Keywords to Block off Well-Performing Keywords
Description of strategy: Once a search term has been converting well in a certain campaign (especially auto, broad, or phrase), you harvest it and move it ("graduate") to an exact match campaign, then block it from the source. A few different names to describe this technique by various authors include "Search Term Isolation" and "Keyword Graduation".
Theory behind the strategy: Auto and Manual-Broad campaigns should be used primarily for research. Once you find winning search terms you should exact match them into a new campaign, and simultaneously block them from the source campaign, so that you can control the bids appropriately, only paying what that keyword is worth. The focus here seems to be keyword profitability more than ad generated sales. This technique also assumes that "closing off the floodgates" in the source campaign will now somehow automatically divert traffic to that keyword in the destination campaign.
Counter argument 1: Why touch something that is performing well in the original spot? Look at it another way. When a new keyword is introduced into a campaign, (let's say an exact match campaign), it starts a brand new life cycle. It's not as if any previous good karma from a previous campaign is going to follow through to its new home. Amazon's algorithms will subject it to the brutal tests of conversion and this keyword will need to prove itself before it can start operating at peak performance. But there's a worse scenario that most people don't think of - that this keyword may not perform well at all because of the dynamics of the existing set of keywords sharing a campaign budget. It's hard to predict precisely how Amazon's algorithms actually work.
Counter argument 2: Why should you block something that is bringing you good sales? An additive approach is smarter. Have more horses in the race. Keep the search term in the source, even after extracting the best search terms.
Counter argument 3: Negative keywords, especially the ones that are actually relevant to your product, will train Amazon to not bring you relevant traffic from similar and related listings. This chart below is from Amazon. It describes the algorithm used for auto target matches, that match not only keywords but also products. Imagine what would happen if you negative keyworded the term "300-count". Expect a drastic cut in traffic from ASINs that include that term.
2. Bid on Your Branded Terms
Description of strategy: Bid on your branded terms so that if someone types your brand name, your ads always show up alongside the organic listings, and take up maximum real estate.
Theory behind the strategy: Amazon is becoming more pay-to-play. The top 3 placements on the SERP are sponsored (headline followed by 2-4 more ads above the fold). "Play defensive" here and don't allow competitors from stealing those spots and mind-share by causing attractive distractions. It's a small price to pay for staying top of mind.
Counter argument: Why pay for bids on your branded name when a buyer has expressed specific intent through their choice of words. They will find your organic listing even though it is embedded somewhere below the fold.
Counter counter-argument: How many times have you, as a buyer, typed a certain brand name and ended up buying some other brand? Think about it.
3. Separate Your Campaigns Based on Match Types
Description of strategy: Build a campaign structure based on keyword match types.
Theory behind the strategy: You have better control over budgets and bids, as well as ease of viewing and analyzing data.
Counter argument: Fair enough, but there are any number of alternative ways to structure your campaigns like so:
Structure 1: Create campaigns such that you can separate keywords based on search volume. Don't mix up high volume keywords with low volume ones because the higher volume keywords will fast consume your budget, starving the rest.
Structure 2: Create campaigns such that you can separate keywords based on phases such as "Discovery", "Research", "Winners". Keep moving keywords across these campaigns.
Structure 3: Create campaigns based on keyword groupings such as "branded keywords", "competitor keywords", "keyword themes" etc.
4. Cut Ad Spend if you are Likely to Run Out of Stock
Description of strategy: If you are likely to run out of stock because of supply chain disruption (say, on account of the #coronavirus) then slow down your sales by increasing prices or cut off traffic by reducing ad spend to reduce the number of visits. Artificially drop sales to hold on to inventory.
Theory behind the strategy: Amazon will punish you for going out of stock, and you will lose your sales rank. So it's better to never run out of stock, keep Amazon happy and maintain sales rank.
Counter argument: While it's better to never run out of stock long term, artificially slowing down sales will negatively train the algorithm into believing that the sales velocity is trending DOWN, and that this is no longer a hot seller. So when you do eventually replenish stocks, you will FIRST have to make Amazon unlearn what it's learnt about your sales velocity, by really cranking up sales. It's an uphill task either ways. A better way might be to run out of stock on a high note (high sales velocity), then turn off your listing to preserve sales rank.
5. Bid Differently on Different Match Types of the Same Keywords
Description of strategy: Broad match should have the lowest bids, followed by a slightly higher bid for phrase match and then the exact match bid is the highest of them all.
Theory behind the strategy: Since broad match keywords cast a wide net, they will attract a very broad set of search audiences, some that may only be remotely associated with your product. On the other hand, exact match keywords are more precise expressions of intent, hence paying higher for them is valid.
Counter argument: Bidding differently on keyword types makes sense, but it shouldn't solely be a function of match type. Instead, you need to factor in tail length and general buyer intent. Let's say, your product is a garlic press. "Garlic press" might be worth way more as a broad match keyword than as exact match because of the variety of potential keyword variations that it can attract, especially with Sponsored Brand ads where broad matches will also attract synonym phrases. Why would you limit the bid here? Keep it higher than exact match if it is serving the purpose. Besides, the best strategy for bidding differently depends so much on the keyword itself. Don't get fooled by a cookie cutter approach. In some cases bidding the same to start with and letting the data guide you might work just fine.
So there you have it. 5 highly contested Amazon PPC strategies that are out there. If there is one thing that you might want to take away from this post, it is that you have to do your own testing of what works and what doesn't for you. This means that you must be wary of tools that bake their own strategies right into the way their tools work, so you have very little say in how your ad dollars are spent, and basically get stuck with them.
When you are starting out, it might be best to go with a tool that does not bind you to any particular PPC strategy. Also, be wary of tools that claim that they are "AI-Based" which might just a hyped-up way of glorifying if-then-else logic statements. First, learn the ropes and be a ninja.
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