SEO
Improve SEM Performance With Your Own Unique KPIs
If you follow me on Twitter, you know I am a harsh critic of those New York Jets and an unsolicited commentator on all things Real Housewives.
But you may have also realized I am a tireless fighter for SEM audience and asset segmentation.
Brand vs. non-brand, first-time consumer vs. repeat visitor, high HHI (high household income) earner women age 25–35 vs. age 65+ coupon shoppers… every element and audience is different.
It makes no sense to hold everything to the same standard for measurement.
One may say, “Jon, I have an aggregate goal. I expect all efforts to hit it. Otherwise, it just isn’t worth running them.”
To which I reply, “Well, riddle me this. How much cheaper is your brand CPC vs. your non-brand, or how much higher is a repeat shoppers conversion rate than a first-timer?”
While you can have an aggregate goal, you still need to realize that every element will perform differently.
Moreover, the different performance levels must combine to funnel into a single performance KPI (Key Performance Indicator).
If you proceeded with nixing all efforts that didn’t meet the aggregate KPI you set across the board, you will fail to garner new customers, and you’ll quickly have a diminishing level of traffic.
Need Proof? Well, Here You Go
Here we observe “client N.”
They are a direct-to-consumer ecommerce brand that sells bacon and assorted smoked meats (yes, it is delicious).
We segment targets on the basic brand vs. non-brand, but also by NTF (first-time purchasers) vs. repeat purchasers.
Our AOV (Average Order Value) is pricing dependent, which is market price dependent, so we focus on maximizing conversion over ROAS (Return On Ad Spend).
We know that we’ll get two to three purchases per year for five years from a customer in a lifetime.
So while getting repeat purchases on our brand is super cost-efficient and pays the bills, we recognize they are now considered a depreciating asset.
As a marketer, do you push heavy on the depreciating assets because it is low cost, or do you pay out the wazoo for a new customer upfront, realizing they will become super cost-efficient on the second purchase?
Spoiler: Never stop supporting the repeat customer, but push hard for the first-time customer.
Because of this, we have six different KPIs (and their reasons):
Brand Repeat
- Low-level CPC KPI.
- Why: They are brand loyal, with a high probability of purchasing, so we want to get the CPC (Cost Per Click) as low as possible to direct them to the product we want to push.
Brand NTF
- High traffic KPI & Mid-level CPC KPI.
- Why: Brand aware, usually a receiver of gift or other marketing, high conversion probability, CPC is pricier, so if we can control it, it’ll be a better LTV ROAS.
Non-Brand Repeat
- CPA (Cost Per Action) KPI.
- They have no loyalty, they purchased once before but didn’t come back to us by name, so it is more logical to focus on a specific CPA target because another purchase after this is much less likely.
- Important to note that this is the least valuable customer and shows a lack of brand loyalty.
Non-Brand NTF
- High Traffic & High Impression Share KPI.
- You want as many of these as possible, and in a crowded marketplace, you often have to surrender cost (because this will not be cheap) for visibility (make sure you have a great ad in place.
- You’ll compensate on the back end for a conversion.
Shopping (We Don’t Separate NTF From Repeat)
- Conversion volume & ROAS KPI.
- This is our moneymaker after brand. Max out your sales volume as much as you can. Clicks are cheaper given the ad unit. Just make sure you don’t dip below a 110% ROAS.
Display/Video
- Brand Awareness KPI.
- This isn’t getting us direct sales. It builds brand awareness, so we do the lowest CPV on our 30-second videos and CPM (Cost Per 1,000 Impressions) on our display and test it regionally to determine the level of inbound first-time brand visitors to the site.
- We harvest the visitors for remarketing.
Another example is “client S.”
They are a chain of senior living communities around the country.
Their focus is on lead generation via form submissions or phone calls of a certain duration.
As always, we sort by brand and non-brand keywords and services provided. Each service has a different lifetime valuation as recurring revenue.
Independent living has a higher volume, longer LTV duration, and lower revenue per resident.
While at the other end of the spectrum, Memory Care is the lowest volume and shorter LTV duration but has the highest initial revenue in the first three years.
In this scenario, we set the KPI by the service line (ignore the lack of brand traffic, it isn’t as concerning for us as each location has a different name).
We operate with three different KPIs:
Independent Living
- High Traffic and mid-low CPC KPI.
- An immense amount of competition, so if you have a good price and a good location, the goal is pure volume. But if the CPC rises (from the competition) above $11, there is a quick chance that clicks fall off a cliff, as there is no additional budget.
Memory Care
- CPA KPI.
- Least amount of competition, but a high degree of researchers, which reduces CTR (Clickthrough Rate) and increases CPC. The key is to focus on the CPA itself with the realization the LTV duration is 25% of Independent Living. The revenue in three years in Memory Care exceeds that of eight years in Independent Living.
Assisted Living
- Low CPC KPI.
- There is a lot of competition, and everyone gets seen as a lot of research goes into this. You don’t have to be in position 1, just be visible, and get the traffic for as little as possible, because, with fixed budgets, a CPC swing of $0.50 can cut your traffic down.
Okay, I’ve Seen Your Proof. Now What?
Once we’ve identified the necessary KPIs, we set the target numbers each to achieve.
This means, things like “Brand Repeat CPC cannot exceed $0.50” or “Non-Brand NTF needs to drive at least 250 clicks per week with an impression share of 15%, and a CPC not exceeding $0.75”.
We then divide the budget from what is most valuable to us to the least for budget distribution.
Then we can determine if the budget allocation will meet the aggregate ROAS objectives.
Takeaway
No two accounts are alike (it’s like calling the Jets and the Giants the same NFL team).
But that being said, not every asset in an account is the same.
Therefore, holding a non-brand first-time searcher of Cherrywood Bacon to the same CTR, CPC, CVR (Conversion Rate), and ROAS of a repeat buy on brand terms buying corned beef hash is like comparing apples to oranges.
Maintaining separate KPI targets, strategies, and elements will lead to a more accurate and predictable performance outcome.
Featured Image: idea Ink Design/Shutterstock
SEO
Why Google Can’t Tell You About Every Ranking Drop
In a recent Twitter exchange, Google’s Search Liaison, Danny Sullivan, provided insight into how the search engine handles algorithmic spam actions and ranking drops.
The discussion was sparked by a website owner’s complaint about a significant traffic loss and the inability to request a manual review.
Sullivan clarified that a site could be affected by an algorithmic spam action or simply not ranking well due to other factors.
He emphasized that many sites experiencing ranking drops mistakenly attribute it to an algorithmic spam action when that may not be the case.
“I’ve looked at many sites where people have complained about losing rankings and decide they have a algorithmic spam action against them, but they don’t. “
Sullivan’s full statement will help you understand Google’s transparency challenges.
Additionally, he explains why the desire for manual review to override automated rankings may be misguided.
Two different things. A site could have an algorithmic spam action. A site could be not ranking well because other systems that *are not about spam* just don’t see it as helpful.
I’ve looked at many sites where people have complained about losing rankings and decide they have a…
— Google SearchLiaison (@searchliaison) May 13, 2024
Challenges In Transparency & Manual Intervention
Sullivan acknowledged the idea of providing more transparency in Search Console, potentially notifying site owners of algorithmic actions similar to manual actions.
However, he highlighted two key challenges:
- Revealing algorithmic spam indicators could allow bad actors to game the system.
- Algorithmic actions are not site-specific and cannot be manually lifted.
Sullivan expressed sympathy for the frustration of not knowing the cause of a traffic drop and the inability to communicate with someone about it.
However, he cautioned against the desire for a manual intervention to override the automated systems’ rankings.
Sullivan states:
“…you don’t really want to think “Oh, I just wish I had a manual action, that would be so much easier.” You really don’t want your individual site coming the attention of our spam analysts. First, it’s not like manual actions are somehow instantly processed. Second, it’s just something we know about a site going forward, especially if it says it has change but hasn’t really.”
Determining Content Helpfulness & Reliability
Moving beyond spam, Sullivan discussed various systems that assess the helpfulness, usefulness, and reliability of individual content and sites.
He acknowledged that these systems are imperfect and some high-quality sites may not be recognized as well as they should be.
“Some of them ranking really well. But they’ve moved down a bit in small positions enough that the traffic drop is notable. They assume they have fundamental issues but don’t, really — which is why we added a whole section about this to our debugging traffic drops page.”
Sullivan revealed ongoing discussions about providing more indicators in Search Console to help creators understand their content’s performance.
“Another thing I’ve been discussing, and I’m not alone in this, is could we do more in Search Console to show some of these indicators. This is all challenging similar to all the stuff I said about spam, about how not wanting to let the systems get gamed, and also how there’s then no button we would push that’s like “actually more useful than our automated systems think — rank it better!” But maybe there’s a way we can find to share more, in a way that helps everyone and coupled with better guidance, would help creators.”
Advocacy For Small Publishers & Positive Progress
In response to a suggestion from Brandon Saltalamacchia, founder of RetroDodo, about manually reviewing “good” sites and providing guidance, Sullivan shared his thoughts on potential solutions.
He mentioned exploring ideas such as self-declaration through structured data for small publishers and learning from that information to make positive changes.
“I have some thoughts I’ve been exploring and proposing on what we might do with small publishers and self-declaring with structured data and how we might learn from that and use that in various ways. Which is getting way ahead of myself and the usual no promises but yes, I think and hope for ways to move ahead more positively.”
Sullivan said he can’t make promises or implement changes overnight, but he expressed hope for finding ways to move forward positively.
Featured Image: Tero Vesalainen/Shutterstock
SEO
56 Google Search Statistics to Bookmark for 2024
If you’re curious about the state of Google search in 2024, look no further.
Each year we pick, vet, and categorize a list of up-to-date statistics to give you insights from trusted sources on Google search trends.
Check out more resources on how Google works:
Learn more
SEO
How To Use ChatGPT For Keyword Research
Anyone not using ChatGPT for keyword research is missing a trick.
You can save time and understand an entire topic in seconds instead of hours.
In this article, I outline my most effective ChatGPT prompts for keyword research and teach you how I put them together so that you, too, can take, edit, and enhance them even further.
But before we jump into the prompts, I want to emphasize that you shouldn’t replace keyword research tools or disregard traditional keyword research methods.
ChatGPT can make mistakes. It can even create new keywords if you give it the right prompt. For example, I asked it to provide me with a unique keyword for the topic “SEO” that had never been searched before.
“Interstellar Internet SEO: Optimizing content for the theoretical concept of an interstellar internet, considering the challenges of space-time and interplanetary communication delays.”
Although I want to jump into my LinkedIn profile and update my title to “Interstellar Internet SEO Consultant,” unfortunately, no one has searched that (and they probably never will)!
You must not blindly rely on the data you get back from ChatGPT.
What you can rely on ChatGPT for is the topic ideation stage of keyword research and inspiration.
ChatGPT is a large language model trained with massive amounts of data to accurately predict what word will come next in a sentence. However, it does not know how to do keyword research yet.
Instead, think of ChatGPT as having an expert on any topic armed with the information if you ask it the right question.
In this guide, that is exactly what I aim to teach you how to do – the most essential prompts you need to know when performing topical keyword research.
Best ChatGPT Keyword Research Prompts
The following ChatGPT keyword research prompts can be used on any niche, even a topic to which you are brand new.
For this demonstration, let’s use the topic of “SEO” to demonstrate these prompts.
Generating Keyword Ideas Based On A Topic
What Are The {X} Most Popular Sub-topics Related To {Topic}?
The first prompt is to give you an idea of the niche.
As shown above, ChatGPT did a great job understanding and breaking down SEO into three pillars: on-page, off-page & technical.
The key to the following prompt is to take one of the topics ChatGPT has given and query the sub-topics.
What Are The {X} Most Popular Sub-topics Related To {Sub-topic}?
For this example, let’s query, “What are the most popular sub-topics related to keyword research?”
Having done keyword research for over 10 years, I would expect it to output information related to keyword research metrics, the types of keywords, and intent.
Let’s see.
Again, right on the money.
To get the keywords you want without having ChatGPT describe each answer, use the prompt “list without description.”
Here is an example of that.
List Without Description The Top {X} Most Popular Keywords For The Topic Of {X}
You can even branch these keywords out further into their long-tail.
Example prompt:
List Without Description The Top {X} Most Popular Long-tail Keywords For The Topic “{X}”
List Without Description The Top Semantically Related Keywords And Entities For The Topic {X}
You can even ask ChatGPT what any topic’s semantically related keywords and entities are!
Tip: The Onion Method Of Prompting ChatGPT
When you are happy with a series of prompts, add them all to one prompt. For example, so far in this article, we have asked ChatGPT the following:
- What are the four most popular sub-topics related to SEO?
- What are the four most popular sub-topics related to keyword research
- List without description the top five most popular keywords for “keyword intent”?
- List without description the top five most popular long-tail keywords for the topic “keyword intent types”?
- List without description the top semantically related keywords and entities for the topic “types of keyword intent in SEO.”
Combine all five into one prompt by telling ChatGPT to perform a series of steps. Example:
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4, and Step 5”
Example:
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4 and Step 5. Step 1 – Generate an answer for the 3 most popular sub-topics related to {Topic}?. Step 2 – Generate 3 of the most popular sub-topics related to each answer. Step 3 – Take those answers and list without description their top 3 most popular keywords. Step 4 – For the answers given of their most popular keywords, provide 3 long-tail keywords. Step 5 – for each long-tail keyword offered in the response, a list without descriptions 3 of their top semantically related keywords and entities.”
Generating Keyword Ideas Based On A Question
Taking the steps approach from above, we can get ChatGPT to help streamline getting keyword ideas based on a question. For example, let’s ask, “What is SEO?”
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, and Step 4. Step 1 Generate 10 questions about “{Question}”?. Step 2 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 3 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 4 – Based on the above Steps 1,2,3 suggest a final list of questions avoiding duplicates or semantically similar questions.”
Generating Keyword Ideas Using ChatGPT Based On The Alphabet Soup Method
One of my favorite methods, manually, without even using a keyword research tool, is to generate keyword research ideas from Google autocomplete, going from A to Z.
You can also do this using ChatGPT.
Example prompt:
“give me popular keywords that includes the keyword “SEO”, and the next letter of the word starts with a”
Tip: Using the onion prompting method above, we can combine all this in one prompt.
“Give me five popular keywords that include “SEO” in the word, and the following letter starts with a. Once the answer has been done, move on to giving five more popular keywords that include “SEO” for each letter of the alphabet b to z.”
Generating Keyword Ideas Based On User Personas
When it comes to keyword research, understanding user personas is essential for understanding your target audience and keeping your keyword research focused and targeted. ChatGPT may help you get an initial understanding of customer personas.
Example prompt:
“For the topic of “{Topic}” list 10 keywords each for the different types of user personas”
You could even go a step further and ask for questions based on those topics that those specific user personas may be searching for:
As well as get the keywords to target based on those questions:
“For each question listed above for each persona, list the keywords, as well as the long-tail keywords to target, and put them in a table”
Generating Keyword Ideas Using ChatGPT Based On Searcher Intent And User Personas
Understanding the keywords your target persona may be searching is the first step to effective keyword research. The next step is to understand the search intent behind those keywords and which content format may work best.
For example, a business owner who is new to SEO or has just heard about it may be searching for “what is SEO.”
However, if they are further down the funnel and in the navigational stage, they may search for “top SEO firms.”
You can query ChatGPT to inspire you here based on any topic and your target user persona.
SEO Example:
“For the topic of “{Topic}” list 10 keywords each for the different types of searcher intent that a {Target Persona} would be searching for”
ChatGPT For Keyword Research Admin
Here is how you can best use ChatGPT for keyword research admin tasks.
Using ChatGPT As A Keyword Categorization Tool
One of the use cases for using ChatGPT is for keyword categorization.
In the past, I would have had to devise spreadsheet formulas to categorize keywords or even spend hours filtering and manually categorizing keywords.
ChatGPT can be a great companion for running a short version of this for you.
Let’s say you have done keyword research in a keyword research tool, have a list of keywords, and want to categorize them.
You could use the following prompt:
“Filter the below list of keywords into categories, target persona, searcher intent, search volume and add information to a six-column table: List of keywords – [LIST OF KEYWORDS], Keyword Search Volume [SEARCH VOLUMES] and Keyword Difficulties [KEYWORD DIFFICUTIES].”
Tip: Add keyword metrics from the keyword research tools, as using the search volumes that a ChatGPT prompt may give you will be wildly inaccurate at best.
Using ChatGPT For Keyword Clustering
Another of ChatGPT’s use cases for keyword research is to help you cluster. Many keywords have the same intent, and by grouping related keywords, you may find that one piece of content can often target multiple keywords at once.
However, be careful not to rely only on LLM data for clustering. What ChatGPT may cluster as a similar keyword, the SERP or the user may not agree with. But it is a good starting point.
The big downside of using ChatGPT for keyword clustering is actually the amount of keyword data you can cluster based on the memory limits.
So, you may find a keyword clustering tool or script that is better for large keyword clustering tasks. But for small amounts of keywords, ChatGPT is actually quite good.
A great use small keyword clustering use case using ChatGPT is for grouping People Also Ask (PAA) questions.
Use the following prompt to group keywords based on their semantic relationships. For example:
“Organize the following keywords into groups based on their semantic relationships, and give a short name to each group: [LIST OF PAA], create a two-column table where each keyword sits on its own row.
Using Chat GPT For Keyword Expansion By Patterns
One of my favorite methods of doing keyword research is pattern spotting.
Most seed keywords have a variable that can expand your target keywords.
Here are a few examples of patterns:
1. Question Patterns
(who, what, where, why, how, are, can, do, does, will)
“Generate [X] keywords for the topic “[Topic]” that contain any or all of the following “who, what, where, why, how, are, can, do, does, will”
2. Comparison Patterns
Example:
“Generate 50 keywords for the topic “{Topic}” that contain any or all of the following “for, vs, alternative, best, top, review”
3. Brand Patterns
Another one of my favorite modifiers is a keyword by brand.
We are probably all familiar with the most popular SEO brands; however, if you aren’t, you could ask your AI friend to do the heavy lifting.
Example prompt:
“For the top {Topic} brands what are the top “vs” keywords”
4. Search Intent Patterns
One of the most common search intent patterns is “best.”
When someone is searching for a “best {topic}” keyword, they are generally searching for a comprehensive list or guide that highlights the top options, products, or services within that specific topic, along with their features, benefits, and potential drawbacks, to make an informed decision.
Example:
“For the topic of “[Topic]” what are the 20 top keywords that include “best”
Again, this guide to keyword research using ChatGPT has emphasized the ease of generating keyword research ideas by utilizing ChatGPT throughout the process.
Keyword Research Using ChatGPT Vs. Keyword Research Tools
Free Vs. Paid Keyword Research Tools
Like keyword research tools, ChatGPT has free and paid options.
However, one of the most significant drawbacks of using ChatGPT for keyword research alone is the absence of SEO metrics to help you make smarter decisions.
To improve accuracy, you could take the results it gives you and verify them with your classic keyword research tool – or vice versa, as shown above, uploading accurate data into the tool and then prompting.
However, you must consider how long it takes to type and fine-tune your prompt to get your desired data versus using the filters within popular keyword research tools.
For example, if we use a popular keyword research tool using filters, you could have all of the “best” queries with all of their SEO metrics:
And unlike ChatGPT, generally, there is no token limit; you can extract several hundred, if not thousands, of keywords at a time.
As I have mentioned multiple times throughout this piece, you cannot blindly trust the data or SEO metrics it may attempt to provide you with.
The key is to validate the keyword research with a keyword research tool.
ChatGPT For International SEO Keyword Research
ChatGPT can be a terrific multilingual keyword research assistant.
For example, if you wanted to research keywords in a foreign language such as French. You could ask ChatGPT to translate your English keywords;
- The key is to take the data above and paste it into a popular keyword research tool to verify.
- As you can see below, many of the keyword translations for the English keywords do not have any search volume for direct translations in French.
But don’t worry, there is a workaround: If you have access to a competitor keyword research tool, you can see what webpage is ranking for that query – and then identify the top keyword for that page based on the ChatGPT translated keywords that do have search volume.
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Or, if you don’t have access to a paid keyword research tool, you could always take the top-performing result, extract the page copy, and then ask ChatGPT what the primary keyword for the page is.
Key Takeaway
ChatGPT can be an expert on any topic and an invaluable keyword research tool. However, it is another tool to add to your toolbox when doing keyword research; it does not replace traditional keyword research tools.
As shown throughout this tutorial, from making up keywords at the beginning to inaccuracies around data and translations, ChatGPT can make mistakes when used for keyword research.
You cannot blindly trust the data you get back from ChatGPT.
However, it can offer a shortcut to understanding any topic for which you need to do keyword research and, as a result, save you countless hours.
But the key is how you prompt.
The prompts I shared with you above will help you understand a topic in minutes instead of hours and allow you to better seed keywords using keyword research tools.
It can even replace mundane keyword clustering tasks that you used to do with formulas in spreadsheets or generate ideas based on keywords you give it.
Paired with traditional keyword research tools, ChatGPT for keyword research can be a powerful tool in your arsenal.
More resources:
Featured Image: Tatiana Shepeleva/Shutterstock
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