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Marketing Analytics: The Simple Guide



Marketing Analytics: The Simple Guide

Marketing analytics is the measurement and analysis of marketing data to seek patterns and insights that can improve marketing performance.

If you’re doing digital marketing, you’re swimming in a vast pool of actionable data. But if you’re not using tools and techniques to discover, analyze, and interpret this data, then you’re swimming with your eyes closed.

To help you learn what marketing analytics can do, we’ll cover the following:

Why marketing analytics is important


First, marketing analytics can answer questions vital to any business, no matter the size. Here are a few common questions: How are our campaigns performing? Are we spending money on the right marketing channels? How do we compare to our competitors?

Knowing those things is great, but it gets even better. Measuring marketing performance opens the door to improving it. For instance, if you notice your PPC campaigns on Facebook are starting to bring less traffic, you can do something about it. You can try improving the ads or even moving your marketing budget elsewhere and then comparing results.

Or maybe you’re in a situation where you need to set goals for yourself, your team, or your contractors. You can base those goals on an analysis of past performance and get a quantifiable reference point. How else will you know if, let’s say, increasing website traffic by 15% in one month is enough or even doable?

Finally, data can help you get your point across because numbers are persuasive. You can use real numbers from your past marketing efforts to prove that you’re positively impacting the business. Marketing analytics can also help make well-grounded predictions that you can use to fuel your marketing strategy, e.g., securing a higher budget for the next quarter.

How to use marketing analytics


Let’s take a look at some of the ways you can use marketing analytics for business growth.

Report on the past

The past is super important to marketers. It’s because the story with marketing usually goes like this: First, you use some marketing tactic. Then you give it some time to generate results. Finally, you check on those results.

On that note, marketing analytics will help you answer questions such as:

  • How much organic traffic did our content generate last quarter?
  • How many new leads did Campaign A generate compared to Campaign B?
  • What was the conversion rate from trial sign-ups to paid subscriptions?
  • What was the average cart abandonment rate last year?

The good news is that more often than not, marketing analytics software does the tracking and measuring of the most popular metrics automatically. But the important thing is to set up those tools as soon as possible to avoid data gaps.

Analyze the present

Marketing analytics can answer some more “timely” questions too, such as things related to patterns in customer behaviors, trends, current budget spending, etc. For example:

  • Why is organic traffic to our blog decreasing?
  • What percentage of our customers use the [feature] of our product?
  • What is the lifetime value of our customers?
  • What is our current ranking for [query] in Google?

And when you’ve got insights into your past performance and present state of affairs, you’re all set to take on a task that marketers are asked to do (but few can deliver) all the time: predict the future.

Predict the future

Enter predictive analytics or, in other words, making data-driven assumptions about what can happen in the future. Predicting the future is why marketers are not simply reporting for reporting’s sake.

For example, if a marketer is able to prove a positive return on investment of a given marketing tactic based on past performance, they can forecast the future performance quite accurately. Often, this is enough to get the marketing budget they need.


Here, we also enter the realm of prescriptive analytics, the type of analytics that answers the question, “What should be done?” For example:

  • Which type of page layout should we use? You can use an A/B testing software to test your options.
  • What type of message should we send to a prospect to increase our chances of converting them? Marketers can build models of optimal conversion paths and then test them by setting up automated email workflows.
  • What keywords should we target in our content? SEOs and content marketers do keyword research for that.

Compare with competitors

Marketing analytics can help you turn your competitors into allies (almost). Thanks to data from various competitive analysis methods, it’s possible to learn from someone’s mistakes or emulate someone’s success.

For example, to identify gaps in your content, you can run a content gap analysis using Ahrefs in just a few clicks and see what keywords your competitors rank for that you don’t.

Content Gap report results

How to start the marketing analytics process (four steps)

Whether you want to perform ad hoc analytics or develop a set of metrics that will appear in recurring reports, this simple four-step process will help you focus on what’s most important.

1. Identify what you want to measure

As you can see in the paragraphs above, there are a lot of different things that marketing analytics software can track and measure for you. But this creates a temptation to just dive in and look for any kind of insight.

While you may find some this way, it’s more effective to determine what you’ll be looking for first and leave less to chance. In other words, if your analytics tool were a person, what questions would you like them to answer?


For example, let’s say you’re investing heavily in creating content designed to rank on Google Search. Since your competitors are doing the same thing, you’ll want to know this: How visible is my content on the SERPs compared to them? This is a metric known as the share of voice (SOV).

So now that we have our sample research question in place, we can move on to the next step.

2. Assess your capabilities

There are two questions to ask here:

  1. Do you have access to quality data?
  2. Do you have the skill to extract and process the data?

And there is no other way to answer these than to learn more about your research question.

This step may sound trivial, but it’s actually a critical one. Because if you dive headfirst into an analytics problem that is best left to someone else (e.g., a data scientist or an external consultant), chances are you will just waste time instead of better spending it on something else.

And this is a common problem among marketing teams. A study revealed that only 1.9% of marketing leaders reported their companies have the right talent to leverage marketing analytics.

Whatever your research question may be, just try Googling it first. It’s likely someone has already created a product or service to solve your problem. For instance, a basic query like “share of voice” could lead you to our how-to article.

Google SERP for "share of voice"

3. Gather data using marketing analytics tools

Continuing our example of calculating SOV, we learn (after doing some quick research online) that you can solve this problem without any special skills by using an SEO tool like Ahrefs. To illustrate, one of the methods consists of three steps:

  1. Set keywords you want to track and paste them into Ahrefs’ Rank Tracker
  2. Set competitors’ domains you want to match against
  3. Go to the Competitors report and see your data automatically calculated and visualized in the “Visibility” tab
Visibility report showing key data. Below is a line graph of the key data on Ahrefs and its competitors

The Visibility report shows what percentage of all clicks for the tracked keywords land on the target websites.

4. Draw conclusions

Rank Tracker’s Visibility report allows you to analyze the present by making comparisons to your competitors, and it even lets you report on the past SOV. You can do even more if you try to find the reasons behind those numbers and come up with some solutions for future improvements. This is even if you’re generally outperforming your competitors at the moment.

Right below the Visibility report, you can see a report of keyword positions in comparison to your competitors’. And if you sort the results by one of your competitors, you will see keywords for which they perform better than you.

List of keywords, as well as corresponding rankings of Ahrefs, Moz, etc. Sorted results show keyword rankings where Moz outperforms Ahrefs

That knowledge is a great starting point for pinpointing underperforming content and then using SEO tactics to improve rankings. Examples:

  • Getting more backlinks
  • Updating content
  • Optimizing page speed
  • Boosting pages with internal links

Basically, in our four-step process, we went from an idea on what to measure to finding exact areas of improvement in our marketing efforts. And that’s the heart of marketing analytics.

Three marketing analytics tools we use at Ahrefs


Data is at the core of Ahrefs’ marketing activities. And as with most SaaS companies, our martech stack consists of many different tools. Here are some that we use for marketing analytics.

1. Ahrefs

Ahrefs is our all-in-one SEO toolset that helps millions of marketers to optimize their content to rank higher and get more traffic from search engines. And since our core marketing tactic is content marketing, Ahrefs is a tool we can’t live without. We use it mainly for:

  • Finding topics to write about.
  • Studying how to structure our blog posts.
  • Choosing which articles to update.
  • Finding outreach prospects.
  • Studying competitors.
  • Monitoring our performance on search engines.
  • Finding technical SEO issues.

To illustrate, let’s take a closer look at the first point from the above list.

We want to help people get better at SEO and marketing, so we create educational content. We study what people want to learn, the traffic potential of those topics, and how hard it would be to rank our content on Google to get that traffic.

Let’s look at an example. Here, we can see that if we write an article about B2B marketing, we will be looking at an estimated monthly organic traffic of 2K in the U.S. alone. We will also likely need links from about 81 websites to rank in the top 10 in that country. And just like that, we have found a data-driven premise to decide whether to target that keyword or not.

Overview for keyword "b2b marketing"

If you’re curious about the details of the keyword research process, check out the video below:


2. Google Search Console

Google Search Console (GSC) is a free SEO tool designed for monitoring and troubleshooting websites’ appearances in search results.

Among many features, GSC shows the exact number of visits from Google’s SERPs to a website. Since only Google can do that with this accuracy (other tools use estimates), we use GSC to mainly monitor the exact amount of organic traffic coming from Google Search to our pages.

With this knowledge, we can improve pages that are decreasing in traffic or try to improve the CTRs of pages that are ranking high but don’t get clicked on as often as they should (in our opinion).

Query "diy seo" with corresponding data, including CTR and position

Thanks to data from GSC, we can easily identify pages with high keyword rankings but low CTRs. For example, an article targeting the keyword “diy seo” could probably do better based on its position.


3. Matomo

Matomo is a web analytics tool that is often regarded as the “ethical alternative” to Google Analytics, as it takes a more progressive stance toward data ownership and privacy. This is also one of the reasons we chose this tool.

Matomo has all the standard features you’ll expect to help you understand where users come from and how they interact with your website. Things like traffic sources, channel attributions, user flows, goal conversions, cohorts, etc. What’s more, it hosts some tools that you can’t find in other popular alternatives.

For example, we found Matomo to be helpful in an experiment where we compared different banner placements on our website. Instead of guessing the best placement, we appended tracking parameters to some links to see the click performance and decide where would make the most sense to keep the banner.

Banner of Ahrefs' SEO course on our "Free Keyword Generator" page

Is this a good spot to place this banner? We let our users decide.

Table showing results of click performances of some pages

Results of our quick experiment. Conclusion: turn off the banner on the worst-performing page.

Final thoughts

In this article, I aimed for a quick, digestible introduction to the world of marketing analytics. And I hope it is enough to get you interested in learning more about this topic. After all, digital marketing is virtually impossible to do without it.


As you dive deeper into marketing analytics, it will get more complicated than what we’ve discussed here. But on the other hand, it gets more interesting too. For example, there are methods where you can use machine learning for prescriptive analytics to uncover areas of improvement.

Also, if you’re interested in data analysis and want to make it one of the pillars of your marketing career, here’s some good news for you: Data-driven marketing is an important trend in the industry; in my opinion, it’s most likely here to stay. So getting some kind of data analytics certification relevant to your specialization is probably a good idea.

On a final note, to implement marketing analytics effectively (especially the more advanced type) in your organization, you will need the buy-in of other stakeholders. In other words, you will need a favorable company culture, aka data culture. Obviously, it’s not the data that matters the most, but what you do with it.

Got questions or comments? Ping me on Twitter.

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Reddit Post Ranks On Google In 5 Minutes




Google apparently ranks Reddit posts within minutes

Google’s Danny Sullivan disputed the assertions made in a Reddit discussion that Google is showing a preference for Reddit in the search results. But a Redditor’s example proves that it’s possible for a Reddit post to rank in the top ten of the search results within minutes and to actually improve rankings to position #2 a week later.

Discussion About Google Showing Preference To Reddit

A Redditor (gronetwork) complained that Google is sending so many visitors to Reddit that the server is struggling with the load and shared an example that proved that it can only take minutes for a Reddit post to rank in the top ten.

That post was part of a 79 post Reddit thread where many in the r/SEO subreddit were complaining about Google allegedly giving too much preference to Reddit over legit sites.

The person who did the test (gronetwork) wrote:

“…The website is already cracking (server down, double posts, comments not showing) because there are too many visitors.

…It only takes few minutes (you can test it) for a post on Reddit to appear in the top ten results of Google with keywords related to the post’s title… (while I have to wait months for an article on my site to be referenced). Do the math, the whole world is going to spam here. The loop is completed.”


Reddit Post Ranked Within Minutes

Another Redditor asked if they had tested if it takes “a few minutes” to rank in the top ten and gronetwork answered that they had tested it with a post titled, Google SGE Review.

gronetwork posted:

“Yes, I have created for example a post named “Google SGE Review” previously. After less than 5 minutes it was ranked 8th for Google SGE Review (no quotes). Just after, 6 authoritative SEO websites and’s overview page for SGE (Search Generative Experience). It is ranked third for SGE Review.”

It’s true, not only does that specific post (Google SGE Review) rank in the top 10, the post started out in position 8 and it actually improved ranking, currently listed beneath the number one result for the search query “SGE Review”.

Screenshot Of Reddit Post That Ranked Within Minutes

Anecdotes Versus Anecdotes

Okay, the above is just one anecdote. But it’s a heck of an anecdote because it proves that it’s possible for a Reddit post to rank within minutes and get stuck in the top of the search results over other possibly more authoritative websites.

hankschrader79 shared that Reddit posts outrank Toyota Tacoma forums for a phrase related to mods for that truck.


Google’s Danny Sullivan responded to that post and the entire discussion to dispute that Reddit is not always prioritized over other forums.

Danny wrote:

“Reddit is not always prioritized over other forums. [super vhs to mac adapter] I did this week, it goes Apple Support Community, MacRumors Forum and further down, there’s Reddit. I also did [kumo cloud not working setup 5ghz] recently (it’s a nightmare) and it was the Netgear community, the SmartThings Community, GreenBuildingAdvisor before Reddit. Related to that was [disable 5g airport] which has Apple Support Community above Reddit. [how to open an 8 track tape] — really, it was the YouTube videos that helped me most, but it’s the Tapeheads community that comes before Reddit.

In your example for [toyota tacoma], I don’t even get Reddit in the top results. I get Toyota, Car & Driver, Wikipedia, Toyota again, three YouTube videos from different creators (not Toyota), Edmunds, a Top Stories unit. No Reddit, which doesn’t really support the notion of always wanting to drive traffic just to Reddit.

If I guess at the more specific query you might have done, maybe [overland mods for toyota tacoma], I get a YouTube video first, then Reddit, then Tacoma World at third — not near the bottom. So yes, Reddit is higher for that query — but it’s not first. It’s also not always first. And sometimes, it’s not even showing at all.”

hankschrader79 conceded that they were generalizing when they wrote that Google always prioritized Reddit. But they also insisted that that didn’t diminish what they said is a fact that Google’s “prioritization” forum content has benefitted Reddit more than actual forums.

Why Is The Reddit Post Ranked So High?

It’s possible that Google “tested” that Reddit post in position 8 within minutes and that user interaction signals indicated to Google’s algorithms that users prefer to see that Reddit post. If that’s the case then it’s not a matter of Google showing preference to Reddit post but rather it’s users that are showing the preference and the algorithm is responding to those preferences.


Nevertheless, an argument can be made that user preferences for Reddit can be a manifestation of Familiarity Bias. Familiarity Bias is when people show a preference for things that are familiar to them. If a person is familiar with a brand because of all the advertising they were exposed to then they may show a bias for the brand products over unfamiliar brands.

Users who are familiar with Reddit may choose Reddit because they don’t know the other sites in the search results or because they have a bias that Google ranks spammy and optimized websites and feel safer reading Reddit.

Google may be picking up on those user interaction signals that indicate a preference and satisfaction with the Reddit results but those results may simply be biases and not an indication that Reddit is trustworthy and authoritative.

Is Reddit Benefiting From A Self-Reinforcing Feedback Loop?

It may very well be that Google’s decision to prioritize user generated content may have started a self-reinforcing pattern that draws users in to Reddit through the search results and because the answers seem plausible those users start to prefer Reddit results. When they’re exposed to more Reddit posts their familiarity bias kicks in and they start to show a preference for Reddit. So what could be happening is that the users and Google’s algorithm are creating a self-reinforcing feedback loop.

Is it possible that Google’s decision to show more user generated content has kicked off a cycle where more users are exposed to Reddit which then feeds back into Google’s algorithm which in turn increases Reddit visibility, regardless of lack of expertise and authoritativeness?

Featured Image by Shutterstock/Kues


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WordPress Releases A Performance Plugin For “Near-Instant Load Times”




WordPress speculative loading plugin

WordPress released an official plugin that adds support for a cutting edge technology called speculative loading that can help boost site performance and improve the user experience for site visitors.

Speculative Loading

Rendering means constructing the entire webpage so that it instantly displays (rendering). When your browser downloads the HTML, images, and other resources and puts it together into a webpage, that’s rendering. Prerendering is putting that webpage together (rendering it) in the background.

What this plugin does is to enable the browser to prerender the entire webpage that a user might navigate to next. The plugin does that by anticipating which webpage the user might navigate to based on where they are hovering.

Chrome lists a preference for only prerendering when there is an at least 80% probability of a user navigating to another webpage. The official Chrome support page for prerendering explains:

“Pages should only be prerendered when there is a high probability the page will be loaded by the user. This is why the Chrome address bar prerendering options only happen when there is such a high probability (greater than 80% of the time).

There is also a caveat in that same developer page that prerendering may not happen based on user settings, memory usage and other scenarios (more details below about how analytics handles prerendering).


The Speculative Loading API solves a problem that previous solutions could not because in the past they were simply prefetching resources like JavaScript and CSS but not actually prerendering the entire webpage.

The official WordPress announcement explains it like this:

Introducing the Speculation Rules API
The Speculation Rules API is a new web API that solves the above problems. It allows defining rules to dynamically prefetch and/or prerender URLs of certain structure based on user interaction, in JSON syntax—or in other words, speculatively preload those URLs before the navigation. This API can be used, for example, to prerender any links on a page whenever the user hovers over them.”

The official WordPress page about this new functionality describes it:

“The Speculation Rules API is a new web API… It allows defining rules to dynamically prefetch and/or prerender URLs of certain structure based on user interaction, in JSON syntax—or in other words, speculatively preload those URLs before the navigation.

This API can be used, for example, to prerender any links on a page whenever the user hovers over them. Also, with the Speculation Rules API, “prerender” actually means to prerender the entire page, including running JavaScript. This can lead to near-instant load times once the user clicks on the link as the page would have most likely already been loaded in its entirety. However that is only one of the possible configurations.”

The new WordPress plugin adds support for the Speculation Rules API. The Mozilla developer pages, a great resource for HTML technical understanding describes it like this:

“The Speculation Rules API is designed to improve performance for future navigations. It targets document URLs rather than specific resource files, and so makes sense for multi-page applications (MPAs) rather than single-page applications (SPAs).

The Speculation Rules API provides an alternative to the widely-available <link rel=”prefetch”> feature and is designed to supersede the Chrome-only deprecated <link rel=”prerender”> feature. It provides many improvements over these technologies, along with a more expressive, configurable syntax for specifying which documents should be prefetched or prerendered.”


See also: Are Websites Getting Faster? New Data Reveals Mixed Results

Performance Lab Plugin

The new plugin was developed by the official WordPress performance team which occasionally rolls out new plugins for users to test ahead of possible inclusion into the actual WordPress core. So it’s a good opportunity to be first to try out new performance technologies.

The new WordPress plugin is by default set to prerender “WordPress frontend URLs” which are pages, posts, and archive pages. How it works can be fine-tuned under the settings:

Settings > Reading > Speculative Loading

Browser Compatibility

The Speculative API is supported by Chrome 108 however the specific rules used by the new plugin require Chrome 121 or higher. Chrome 121 was released in early 2024.

Browsers that do not support will simply ignore the plugin and will have no effect on the user experience.

Check out the new Speculative Loading WordPress plugin developed by the official core WordPress performance team.


How Analytics Handles Prerendering

A WordPress developer commented with a question asking how Analytics would handle prerendering and someone else answered that it’s up to the Analytics provider to detect a prerender and not count it as a page load or site visit.

Fortunately both Google Analytics and Google Publisher Tags (GPT) both are able to handle prerenders. The Chrome developers support page has a note about how analytics handles prerendering:

“Google Analytics handles prerender by delaying until activation by default as of September 2023, and Google Publisher Tag (GPT) made a similar change to delay triggering advertisements until activation as of November 2023.”

Possible Conflict With Ad Blocker Extensions

There are a couple things to be aware of about this plugin, aside from the fact that it’s an experimental feature that requires Chrome 121 or higher.

A comment by a WordPress plugin developer that this feature may not work with browsers that are using the uBlock Origin ad blocking browser extension.

Download the plugin:
Speculative Loading Plugin by the WordPress Performance Team

Read the announcement at WordPress
Speculative Loading in WordPress


See also: WordPress, Wix & Squarespace Show Best CWV Rate Of Improvement

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10 Paid Search & PPC Planning Best Practices




10 Paid Search & PPC Planning Best Practices

Whether you are new to paid media or reevaluating your efforts, it’s critical to review your performance and best practices for your overall PPC marketing program, accounts, and campaigns.

Revisiting your paid media plan is an opportunity to ensure your strategy aligns with your current goals.

Reviewing best practices for pay-per-click is also a great way to keep up with trends and improve performance with newly released ad technologies.

As you review, you’ll find new strategies and features to incorporate into your paid search program, too.

Here are 10 PPC best practices to help you adjust and plan for the months ahead.


1. Goals

When planning, it is best practice to define goals for the overall marketing program, ad platforms, and at the campaign level.

Defining primary and secondary goals guides the entire PPC program. For example, your primary conversion may be to generate leads from your ads.

You’ll also want to look at secondary goals, such as brand awareness that is higher in the sales funnel and can drive interest to ultimately get the sales lead-in.

2. Budget Review & Optimization

Some advertisers get stuck in a rut and forget to review and reevaluate the distribution of their paid media budgets.

To best utilize budgets, consider the following:

  • Reconcile your planned vs. spend for each account or campaign on a regular basis. Depending on the budget size, monthly, quarterly, or semiannually will work as long as you can hit budget numbers.
  • Determine if there are any campaigns that should be eliminated at this time to free up the budget for other campaigns.
  • Is there additional traffic available to capture and grow results for successful campaigns? The ad platforms often include a tool that will provide an estimated daily budget with clicks and costs. This is just an estimate to show more click potential if you are interested.
  • If other paid media channels perform mediocrely, does it make sense to shift those budgets to another?
  • For the overall paid search and paid social budget, can your company invest more in the positive campaign results?

3. Consider New Ad Platforms

If you can shift or increase your budgets, why not test out a new ad platform? Knowing your audience and where they spend time online will help inform your decision when choosing ad platforms.

Go beyond your comfort zone in Google, Microsoft, and Meta Ads.


Here are a few other advertising platforms to consider testing:

  • LinkedIn: Most appropriate for professional and business targeting. LinkedIn audiences can also be reached through Microsoft Ads.
  • TikTok: Younger Gen Z audience (16 to 24), video.
  • Pinterest: Products, services, and consumer goods with a female-focused target.
  • Snapchat: Younger demographic (13 to 35), video ads, app installs, filters, lenses.

Need more detailed information and even more ideas? Read more about the 5 Best Google Ads Alternatives.

4. Top Topics in Google Ads & Microsoft Ads

Recently, trends in search and social ad platforms have presented opportunities to connect with prospects more precisely, creatively, and effectively.

Don’t overlook newer targeting and campaign types you may not have tried yet.

  • Video: Incorporating video into your PPC accounts takes some planning for the goals, ad creative, targeting, and ad types. There is a lot of opportunity here as you can simply include video in responsive display ads or get in-depth in YouTube targeting.
  • Performance Max: This automated campaign type serves across all of Google’s ad inventory. Microsoft Ads recently released PMAX so you can plan for consistency in campaign types across platforms. Do you want to allocate budget to PMax campaigns? Learn more about how PMax compares to search.
  • Automation: While AI can’t replace human strategy and creativity, it can help manage your campaigns more easily. During planning, identify which elements you want to automate, such as automatically created assets and/or how to successfully guide the AI in the Performance Max campaigns.

While exploring new features, check out some hidden PPC features you probably don’t know about.

5. Revisit Keywords

The role of keywords has evolved over the past several years with match types being less precise and loosening up to consider searcher intent.

For example, [exact match] keywords previously would literally match with the exact keyword search query. Now, ads can be triggered by search queries with the same meaning or intent.

A great planning exercise is to lay out keyword groups and evaluate if they are still accurately representing your brand and product/service.


Review search term queries triggering ads to discover trends and behavior you may not have considered. It’s possible this has impacted performance and conversions over time.

Critical to your strategy:

  • Review the current keyword rules and determine if this may impact your account in terms of close variants or shifts in traffic volume.
  • Brush up on how keywords work in each platform because the differences really matter!
  • Review search term reports more frequently for irrelevant keywords that may pop up from match type changes. Incorporate these into match type changes or negative keywords lists as appropriate.

6. Revisit Your Audiences

Review the audiences you selected in the past, especially given so many campaign types that are intent-driven.

Automated features that expand your audience could be helpful, but keep an eye out for performance metrics and behavior on-site post-click.

Remember, an audience is simply a list of users who are grouped together by interests or behavior online.

Therefore, there are unlimited ways to mix and match those audiences and target per the sales funnel.

Here are a few opportunities to explore and test:

  • LinkedIn user targeting: Besides LinkedIn, this can be found exclusively in Microsoft Ads.
  • Detailed Demographics: Marital status, parental status, home ownership, education, household income.
  • In-market and custom intent: Searches and online behavior signaling buying cues.
  • Remarketing: Advertisers website visitors, interactions with ads, and video/ YouTube.

Note: This varies per the campaign type and seems to be updated frequently, so make this a regular check-point in your campaign management for all platforms.

7. Organize Data Sources

You will likely be running campaigns on different platforms with combinations of search, display, video, etc.

Looking back at your goals, what is the important data, and which platforms will you use to review and report? Can you get the majority of data in one analytics platform to compare and share?

Millions of companies use Google Analytics, which is a good option for centralized viewing of advertising performance, website behavior, and conversions.

8. Reevaluate How You Report

Have you been using the same performance report for years?

It’s time to reevaluate your essential PPC key metrics and replace or add that data to your reports.

There are two great resources to kick off this exercise:


Your objectives in reevaluating the reporting are:

  • Are we still using this data? Is it still relevant?
  • Is the data we are viewing actionable?
  • What new metrics should we consider adding we haven’t thought about?
  • How often do we need to see this data?
  • Do the stakeholders receiving the report understand what they are looking at (aka data visualization)?

Adding new data should be purposeful, actionable, and helpful in making decisions for the marketing plan. It’s also helpful to decide what type of data is good to see as “deep dives” as needed.

9. Consider Using Scripts

The current ad platforms have plenty of AI recommendations and automated rules, and there is no shortage of third-party tools that can help with optimizations.

Scripts is another method for advertisers with large accounts or some scripting skills to automate report generation and repetitive tasks in their Google Ads accounts.

Navigating the world of scripts can seem overwhelming, but a good place to start is a post here on Search Engine Journal that provides use cases and resources to get started with scripts.

Luckily, you don’t need a Ph.D. in computer science — there are plenty of resources online with free or templated scripts.

10. Seek Collaboration

Another effective planning tactic is to seek out friendly resources and second opinions.


Much of the skill and science of PPC management is unique to the individual or agency, so there is no shortage of ideas to share between you.

You can visit the Paid Search Association, a resource for paid ad managers worldwide, to make new connections and find industry events.

Preparing For Paid Media Success

Strategies should be based on clear and measurable business goals. Then, you can evaluate the current status of your campaigns based on those new targets.

Your paid media strategy should also be built with an eye for both past performance and future opportunities. Look backward and reevaluate your existing assumptions and systems while investigating new platforms, topics, audiences, and technologies.

Also, stay current with trends and keep learning. Check out ebooks, social media experts, and industry publications for resources and motivational tips.

More resources: 


Featured Image: Vanatchanan/Shutterstock

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