On-SERP SEO: The Future of SEO

The SEO game is changing. Long gone are the days when all it took to rank on Page 1 was a good keyword choice and a few backlinks. Google’s search results are becoming so much more than 10 blue links, in part because those links are now richer and more interactive—and sending fewer clicks to […]

The post On-SERP SEO: The Future of SEO appeared first on CXL.

The SEO game is changing. Long gone are the days when all it took to rank on Page 1 was a good keyword choice and a few backlinks.

Google’s search results are becoming so much more than 10 blue links, in part because those links are now richer and more interactive—and sending fewer clicks to sites.

A new concept is replacing the traditional SEO approach. Instead of monitoring and improving organic rankings alone, you need to embrace a more integrated strategy: on-SERP SEO.

You’ll be able to get more business value from each user query, regardless of whether that query generates a click to any website. Here’s how to do it.

What is on-SERP SEO?

On-SERP SEO is a multi-faceted SEO strategy that focuses on occupying as much real estate within each target Google SERP as possible.

It’s also about taking each search query as a whole, instead of optimizing for and monitoring a single position.

Let me explain this via an example. If you search for “pizza” on a mobile device, here’s what you get:

example of features on a mobile search result.
You can see the full SERP here.

Can you see any traditional organic (i.e. blue, clickable) links here? Do you see the point I’m trying to drive home? Organic rankings are no longer enough for organic visibility.

Instead of working on getting listed within organic rankings, you must now consider:

  • Appearing in the featured snippet box (or not, more on that below);
  • Have video show up in the video carousel;
  • Get listed as a related entity (i.e. brand);
  • Ensure your site shows up if a user clicks any of the “related searches”;
  • Have content for the “Interesting finds” section;
  • And, if you own a pizza restaurant, show up as a local business if a user searches nearby.

Each Google SERP is unique and requires an original approach to try and get as much exposure for your brand as possible.

Why is on-SERP SEO such a hot topic?

On-SERP SEO isn’t a new concept, but as Google SERPs become richer and more interactive, focusing only on the standard 10 positions is—and will continue to become—less and less useful. You need your brand to be out there, everywhere, every time a user types in a relevant query.

Things can get even more complicated. For example, ever since Google’s featured snippets got de-duplicated in 2019, there’s no longer a simple answer to a seemingly simple question: Should I rank #1 for my target query?

Google’s featured snippet deduplication means removing a page from organic results once it gets featured. So, if your page was previously ranking first organically and held the featured snippet, it now retains only the featured snippet.

Is that a big deal? You still appear atop Google, right? Well, not all organic listings are created equal. Every featured snippet looks different, and, consequently, there’s no way to know which are more likely to trigger clicks.

In fact, some featured snippets have a much lower click-through rate than top organic positions:

average click-through rate of featured snippets.
Being featured may mean losing over 50% of clicks nowadays. (Image source)

When your page gets featured, you may find yourself wishing you instead ranked among the standard organic results, even if that’s now considered the second position. 

And yet, it remains a tough choice: Do you want your pages to get featured and appear atop all organic results, or would you prefer an organic listing?

This is where the concept of on-SERP SEO comes into play. You should make these decisions on a SERP-by-SERP basis:

What is more clickable?

  1. An information-based featured snippet filled with third-party information (e.g., someone else’s image, links to related topics, etc.) that appears first;
  2. A rich snippet signifying a commercial intent, with every bit clickable and leading to your site.

This may be up for testing, but in this case, I’d take the rich snippet, even though it shows up under the featured snippet:

featured snippet versus rich snippet below.

Next question. What other search elements should you optimize for within this particular search result?

example of various serp features for cat good queries.
All other search elements to optimize for (beyond organic listings): Related questions, popular products, recipes, and search suggestions.

This kind of analysis is what we need to do for each of our core target queries.

How to optimize for on-SERP SEO

Your first step is to identify which content assets and tactics can help you optimize for each query. The exact type of content that’s most useful varies based from one search results page to the next.

So, your first step is to search for your target query in Google—using both desktop and mobile browsers—to identify your best course of action. (If you’re trying to scale this process, think of query syntax, not just queries, something Kevn Indig details here.)

Currently, Google SERPs consist of two groups of elements:

  1. On-SERP elements we can optimize for;
  2. On-SERP elements that change buyer journeys.

1. On-SERP elements we can optimize for

Google has added features to search results that, based on its data, are helpful for searchers. For some SERPs, these features may be images blended into SERPs; for others, they may be news sections, shopping results, etc.

Let’s discuss the most frequent elements that we can optimize for to generate more brand visibility within one search journey.

1.1. Video carousels

Video carousels show up for an overwhelming number of search queries, both on mobile and desktop results. They also take up a good deal of SERP real estate, especially on mobile devices.

On mobile SERPs, Google often generates a clickable timeline of the video, which allows users to click through to a part of the video that covers a specific point:

example of video carousel and specific clickable moments.

When it comes to on-SERP SEO, video carousels are an obvious and easy search element to target. YouTube videos are quite easy to optimize for in Google’s carousels, so I always recommend creating a video version of each and every content asset you create. 

With tools like InVideo, this process is a breeze. It takes literally minutes to turn your text content into a professional-looking video:

  • Select “Article-to-Video” option, and copy-paste your takeaways.
  • Select a template.
  • Once the tool generates your video, edit it to add your own images (e.g., screenshots) and make sure everything looks good.

By default, your video includes subtitles and transitions (good) but also stock photos and background music (not so good). You can change and adjust everything, depending on how much time you want to spend on it.

It’s easy to see where this strategy can be abused, but it’s also easy to imagine its value for a process-driven post with tons of screenshots or GIFs.

invideo screenshot.

1.2. Image results

Images are also popular search elements that sometimes take up the whole above-the-fold part of the screen.

example of search result dominated by images.
Sometimes when you search, all you can see is images on top of organic results.

There’s no specific trick to appearing in this section, apart from implementing basic image SEO and generally making sure you have images on each page of your site.

A cohesive branding strategy for your visuals is a good idea, though. Those images may not warrant a click, but they may help searchers recognize and remember your brand. Make sure all images on your site include your logo and follow a recognizable style. 

1.3. Recipe carousels

Recipe carousels show up for just about any food-related query. 

example of recipe carousel for food query.

If you post recipes on your site, using Recipe schema will help your content get included into in-SERP recipe carousels. All of the recipe plugins listed here support schema, so optimizing for this search element is quite doable.

1.4. Local packs

Local packs dominate search results whenever Google expects users to go and do something locally.

example of local pack results for query.
The local map pack lists the three businesses Google considers most relevant to the query and searcher’s location.

Your site can appear there only if you have a local business that you’ve verified through Google My Business.

1.5. Google Shopping results

Google Shopping results show up within general Google searches, when Google believes there’s a commercial (buying) intent behind a search query. These results normally appear in a special box labeled “Sponsored”:

google shopping results.

To get your products to appear in the box, you need to become part of Google Actions project.

1.6. Interesting finds

“Interesting finds” is a somewhat mysterious search element that appears only on mobile devices.

interesting finds section on mobile results page.

These seem to be random articles on a topic that got traction within an industry. It looks like Google’s attempt to curate great content beyond the traditional ranking factors.

To improve your odds of appearing here, create all kinds of interesting content around your target topic, including history, how-to’s, listicles, etc.

2. On-SERP elements that change buyer journeys

Apart from actual search results, Google has been busy adding search suggestions and interactive sections that, ostensibly, help users more fully research topics.

In reality, these are simply driving people away from clicking search results and prompting them to continue interacting with Google’s search pages.

example of movie search that continues to answer questions on the serp.
These search elements simply trigger more Google searches. Clicking them takes you to more search results instead of taking them to publishers’ sites.

Your task as an optimizer is to try and track down the possible paths users may take after searching for your target query. All of those extra searches should be an additional source of keyword data.

Tools like our featured snippet tool collects Google’s related search suggestions that show up for your important queries and allow you to create content around them:

example of related search data in seo tool.
Find search suggestions that are likely to change your target customers’ searching behavior and optimize your content for them.

You can also get a good glimpse into all kinds of search suggestions using this free browser plugin that creates a nice summary of all search elements underneath each search results page:

related queries via browser plugin.
Search suggestions Google shows for [amazon] search query.

Some of the search sections can be both elements to optimize for and elements triggering more on-SERPs actions. 

For example, “People Also Ask” boxes are incredibly interactive and distracting. (I always spend a lot of time uncovering more and more questions.) Yet they can still send some clicks to pages that answer each individual question, so you want to rank for as many as possible:

people also ask with additional answers on google.
People Also Ask boxes provide additional opportunities for clicks and sources for keyword inspiration.

To increase your chances to rank in a People Also Ask box, embrace a question optimization strategy:

For question research and optimization, you can use a tool like Text Optimizer, which helps you identify popular questions around any search query and then build optimized content around them:

text optimizer tool to find questions people ask on search.
Text Optimizer is the semantic research platform that helps you identify popular niche questions and related concepts to optimize content.

Streamlining and monitoring your on-SERP SEO efforts

At the end of the day, it all comes down to diversifying your content marketing strategy:

  • Where you’d usually write an article, now you need to accompany it with a video and graphics.
  • If previously you’d focus only on tightly related articles to bring leads down the sales funnel, now you need to broaden your topics to educate and inform your target audience.

Buyer journeys are getting more complicated and diverse, so your marketing strategy should, too. It’s mostly good news for a content marketer, as brands need more content and content types than ever before. A content marketer’s job is becoming more integrated and exciting.

It’s harder, however, to measure and report on results. The path between landing on a site and converting has gotten more convoluted and, thus, harder to analyze.

If you’ve struggled to build funnels in Google Analytics, newer tools like Finteza can help. It focuses on monitoring conversion funnels across various channels and devices. You can point the tool to important conversion metrics, and it shows which steps leak traffic or where you could shorten the conversion path.

finteza funnel.
Finteza helps you monitor your site users’ path across the site helping you understand how people are interacting with your content.

You can limit results by traffic source or landing page to better monitor how your on-SERP SEO is paying off.

Conclusion

Google’s richer and more interactive search results require a content marketing and SEO strategy that follows suit. It’s no longer enough to target and monitor organic rankings alone.

You need to evaluate each search result page as a whole. Try to appear in several search sections beyond (yet still including) organic listings. This strategy of optimizing for as many search elements as possible within one SERP is the new normal and the core of on-SERP SEO.

For each SERP, ask:

  • Do I want my page to be featured, or would I rather keep my standard organic listing?
  • Can my images be better branded—explicitly or via subtle but consistent design choices?
  • Which content types or structured markup elements do I need to rank in more search sections?
  • Which topics and search queries does Google associate with my target keyword through related searches, “People Also Ask”, “Interesting finds”, and other sections?

Finally, you’re tasked with monitoring these changes, which is more than just reporting on keyword rankings and organic traffic.

Overall, on-SERP SEO represents both a challenge and added potential—including the potential to boost content quality, brand reputation, loyalty, engagement, and more.

The post On-SERP SEO: The Future of SEO appeared first on CXL.

30+ Killer New Content Ideas in 30 Minutes (and How to Prioritize Them)

Every marketing team needs fresh content ideas.  Maybe you’ve been producing content on the same subject for so long that your idea well has run dry.  Or maybe it’s your keyword well that’s reaching its limits, leaving you with plenty of ideas, but no clear path forward about how to prioritize them or the distribution […]

The post 30+ Killer New Content Ideas in 30 Minutes (and How to Prioritize Them) appeared first on CXL.

Every marketing team needs fresh content ideas. 

Maybe you’ve been producing content on the same subject for so long that your idea well has run dry. 

Or maybe it’s your keyword well that’s reaching its limits, leaving you with plenty of ideas, but no clear path forward about how to prioritize them or the distribution channels for which they’re best suited.

Whatever the case may be, the process covered in this article will help you identify new ideas. It will also ensure you align your content creation efforts with your marketing and business goals.

Content planning for sales and marketing goals

By now, you’re probably sick of reading about tying content ideation and execution to the stages of the classic sales funnel. I’m sick of writing about it, and I think we all know by now that users rarely follow a linear path through a funnel in the first place.

But the linear funnel model still has value from a content planning perspective. Each stage ties roughly to different marketing or business goals. So if you’re trying to decide where or how to allocate your content marketing efforts, knowing your biggest goals (or glaring weaknesses) can help you prioritize.

We’ll use a four-stage funnel model with the following steps:

  • Awareness, which focuses on visibility, education, and inspiration to draw new prospects into further engagement with your company.
  • Evaluation, where differentiation between competitors must occur.
  • Purchase, in which the decision to buy is made.
  • Post-Purchase, where buyers confirm whether they made the right decision to buy from you.
four-stage marketing funnel.

Within this model, if your goals are to grow your traffic, improve brand awareness, or drive initial engagement, you’ll be best served by focusing on the Awareness stage, which includes (but isn’t limited to) content types like:

If, instead, you’re focused on increasing total leads, marketing qualified leads (MQLs), or sales qualified leads (SQLs), your efforts should support the Evaluation stage, with content types such as:

  • Gated case studies;
  • Gated whitepapers;
  • Gated lead magnets;
  • Content upgrades;
  • Webinars;
  • Explainer videos.

If driving revenue or new customer sign-ups is top priority, focus on building content that bolsters the Purchase stage of the funnel, such as:

And finally, if you’re dialed in on increasing referrals or positive reviews, accelerating recognition of value, or minimizing churn, then you’ll want to allocate your efforts toward the Post-Purchase stage, with content including:

A healthy funnel includes content to support each stage. If you’re working with a limited budget, you can focus your brainstorming and creative efforts on content that supports:

  • Your highest priority funnel stage;
  • Multiple funnel stages.

Case studies, for example, can contribute to both the Evaluation and Purchase stages.

Ideation exercise: Brainstorming 30+ new topics

Throughout the rest of the article, I’ll give you 15 questions to use as brainstorming prompts. Not all may apply to you, your company, your industry, your customers, or your business.

But set aside at least 30 minutes for this exercise and try to write down at least two new ideas for each question (or more if you plan to focus on a limited number of funnel stages). 

Awareness

1. What questions are your customers asking?

Marcus Sheridan is the king of the question, having used question-driven content to save his failing River Pools & Spa business during the Great Recession of 2008.

He’s got more on the tactic in his new book, They Ask You Answer, but at its core, it’s a simple concept: Find out which questions your customers are asking, and answer them through content.

(Third-party tools estimate a Domain Rating of 72 and 90,000 monthly organic visitors—virtually unheard of for a small, mainly local business.) 

Not only can doing so help move customers into your sales funnel, it can increase your odds of winning a featured snippet if you build content around question-centric queries.

Potential questions can come from plenty of sources, including:

  • Search queries driving organic traffic;
  • Internal search queries;
  • Your sales team;
  • Your customer service team;
  • Your R&D team.

Ask around. If you can source questions from members of other departments within your company, you may also be able to recruit them to produce the content, minimizing the creative burden on you or your team.

2. What pain points are your customers experiencing?

While you’re speaking with your sales team, ask about specific pain points they sell against (if you haven’t already captured these in your buyer personas).

Content produced around pain points has a high likelihood of resonating with your prospective customers, as it naturally builds rapport by speaking to their experiences. Because this is TOFU content, it shouldn’t feel “salesy.”

Approach pain points from a helpful, educational, or even inspirational perspective. 

Here’s an example of the kind of content this prompt can lead to:

For extra impact, loop back with your sales team after producing pain point content so that they can use the finished work in future sales campaigns.

3. What background knowledge do customers need to use your product or service?

Take several steps back and capture the background knowledge that customers need to be successful with your offering.

Take Mailshake, an email marketing automation program. If you were thinking about the types of education customers need, you’d probably think of things like building email campaigns, scheduling messages, and automating replies.

But on an even more basic level, they need to know how to write a good email. Mailshake’s Cold Email Academy pillar page is a great example of a resource that fulfills this need:

Not only is this type of resource valuable to new customers whose email copywriting skills need practice, it’s also useful for prospects who aren’t sure they’re ready for an email marketing automation program. When they are, this is the kind of resource they’re going to remember.

4. What gaps exist in available education and resources in your industry?

Brian Dean built Backlinko by exploiting a need for digital marketing content that didn’t just give advice but backed it up with research and experiential data.

What similar gaps exist in your industry? What resources would your customers benefit from (that they may not even know they need)? Finding and exploiting these gaps can go a long way toward building not just awareness-stage interest but perceived thought leadership as well. 

5. What knowledge is second-nature to you that your customers don’t know?

This is one of my favorite questions to ask when it comes to TOFU content ideation. Most organizations are sitting on a wealth of internal knowledge they don’t realize they possess.

It’s an inherent challenge of expertise: Once you’re sufficiently advanced, you’ve likely forgotten more about your chosen subject matter than most beginners know in the first place.

As an example, a podcast hosting company I worked with had invested plenty of resources into creating in-depth guides on advanced-level topics, such as producing and marketing podcasts

podcast equipment.

But the awareness-stage customers they were attracting had even more basic needs. They needed to know what equipment to buy to start recording or where to host their finished files—two topics the hosting company had assumed their clients would already understand.

Creating content around these topics filled a need for prospective customers and prevented them from leaving the site to seek information elsewhere.

One big benefit of bringing a beginner’s mind to content ideation is that this type of content is incredibly easy to produce. You already have the expertise. All you need to do is package it up.

Evaluation

6. Where is your industry heading, and what future trends can you comment on?

People like to follow experts. They want to work with them. And one of the fastest ways to establish yourself as an authority is by reflecting thoughtfully on the issues you expect to affect your industry and offering guidance to your audience on how they should prepare or react. 

This isn’t about newsjacking or cranking out some no-value-added resource round-up. It’s about identifying opportunities to position yourself as an expert using insight you already have, so that when your company is held up against its competitors, you come out ahead as the de facto thought leader.

You can do that by:

  • Actually interviewing experts—email answers tend to be cursory, with no chance to ask follow-up questions.
  • Create a narrative, not a laundry list of ideas. Which themes come up again and again? Where do respondents agree or disagree?

7. What do others in your industry get wrong, and—without bashing—how can you set the record straight?

A while back, I worked with a woman whose boutique personal training studio was being threatened by a CrossFit facility that had recently opened up in her area. At one point, a customer who’d tried both facilities shared with my client that the owner of the CrossFit gym had advised him that stretching wasn’t really worthwhile—a perspective my client didn’t share.

I’m not a personal trainer, so I can’t comment on the importance of stretching. (And the last thing I want is to get on the wrong side of CrossFit enthusiasts!) But what I encouraged my client to do was to produce a well-researched, academic-sources-cited content piece backing up her stance on stretching.

The result? Not only was she able to enhance her perception as an authority on the topic, she offered up a compelling reason for prospective clients to work with her over her competitor. 

Don’t use content to trash your competitors. But do look for opportunities to use it to differentiate yourself and to communicate or reinforce your value proposition.

8. How do your products or services stack up to your competitors?

At the evaluation stage, your prospects are comparing you to your competitors. Why not help them along with comparison content?

Here’s an example from Hubspot’s website, comparing Hubspot with Marketo:

The full page is much longer, but the table above elegantly displays how comparison content allows you to help prospects frame their view of your brand.

That said, the caveat here is that comparison content works only if you give both options a fair shake. Lying about features or being deliberately misleading damages the trust prospects are forming with your company.

(On the other hand, for products that are tangentially related to your own, you’re an impartial judge. You can exploit that to create trusted comparison content that the companies involved in the comparison likely can’t.)

9. Is there anything special about your staff, facilities or community involvement that you could translate into benefits for your customers?

Meet Louie, the therapy dog in residence at Smith-North Little Rock Funeral Home, and the star of some of the business’s most popular Facebook posts:

Understandably, funeral homes have a fine line to walk when it comes to creating content. The approach Smith Family Funeral Homes has taken is to share uplifting stories about staff and their community involvement, primarily on the Facebook pages of its funeral home branches.

As a result, not only do they rarely run out of ideas for new content, but families in their community recognize their brand for its involvement, giving them an advantage over other funeral homes in the area.

Don’t engage in community service for the sole purpose of creating content. But if you happen to have exceptional staff or facilities, or if you’re active in your community—whether that means your local area, networks within your industry, or other affiliate groups—use it to fuel content efforts that celebrate these differentiating factors.

Purchase

10. What objections do your customers have, and how do you respond?

In his sales trainings, John Barrows talks about how impactful it can be to address prospects’ objections before they even bring them up. The great news is that it doesn’t have to be your salespeople leading these difficult conversations—your content can do it for them.

Here’s a blog post from Savoya, an executive car service, that handles its potential pricing objection upfront by framing the conversation in the context of ROI:

Since some estimates suggest that 20% of buyers don’t even want to hear from sales until they’re in the Purchase stage, content like this lessens the chances that your company will be taken out of consideration due to objections sales could have otherwise overcome. 

11.  How do your customers benefit from your products or services, and what stories can you tell about their successes?

Obviously, this is a clear opportunity for case studies. But too many companies think of case studies as one-and-done content pieces. Once you’ve captured your customer’s success story, there are plenty of ways you can extend its value, including:

  • Producing shorter case study variants that speak to different pain points or that are more relevant to different audiences (while still drawing from the same source material);
  • Creating a companion content piece that goes into more detail on the behind-the-scenes work your company did to contribute to your customer’s success;
  • Pulling out high-impact quotes for use on your website, in social media graphics, or even email signatures;
  • Integrating it into your sales team’s cadence (or requesting your case study subject use it when making warm introductions to your company);
  • Inviting your case-study subject to join you in creating a conference presentation or podcast interview based on your work together.

These strategies won’t all be appropriate in every situation, but it’s important to remember that consumers engage with stories in different ways. The more opportunities you can identify to share your customer’s successes with them, the more likely it is that they’ll receive your message.

12. What kind of reviews/social praise do you receive, and why do people say that about you?

You’re likely already using the reviews and praise you receive as testimonials in your sales collateral or as social proof on your website. But one underrated opportunity for using this good will is to create content that explains why you get such rave reviews.

example of social proof.

For example, imagine that a common theme running through your company’s reviews is praise for your exceptional customer service. Chances are that didn’t happen by accident. So why not create a content piece that explains the steps you’ve taken to ensure customers’ needs are met?

This hypothetical content piece might include things like:

  • The overarching philosophy you’ve developed that guides your delivery of customer service;
  • How you qualify customer service candidates when hiring;
  • Specific training they undergo;
  • Metrics to which you hold your customer service reps accountable;
  • Mistakes you’ve made in the past, and the lessons you’ve learned as a result.

Show your work. Helping customers see behind the scenes will make you more memorable and trustworthy.

13.  How do you take the risk out of making a purchase decision with your company?

Content pieces about your 30-day money back guarantee aren’t going to move the needle. Instead, think about the underlying fears that keep prospects from pulling the trigger with your company:

  • Are they scared that they won’t see a positive ROI from their investment?
  • Have they been burned in the past when purchasing similar products?
  • Are they worried about missing important goals if they don’t choose the right solution?

These types of fears are fertile ground for content ideation. Could you tell the story of another customer who had failed before finding success with your product? Could you create content that walks prospects through the systems, policies, or procedures you’ve put in place to ensure they get good results with your offering?

Show prospects that you understand the risk that they’re taking on when buying from someone new, and that you’ve taken the steps necessary to ensure their fears are unwarranted.

Post-purchase

14. What do new customers need to know from you to get to their first moment of value as quickly as possible?

SaaS readers will already be familiar with the idea of “first moment of value,” but it’s relevant to every type of business. 

According to Baremetrics, “value,” in this context, is, “the benefit your customer is expecting to receive from your product.”

How long it takes a new customer to realize this value has a significant impact on how happy they are with the purchase they’ve made (and, correspondingly, how likely they are to ask for a refund, refer you to others, or leave a positive review).

It’s up to you to identify your company’s specific first moment of value, but once you know what it is, you can use content to speed new customers toward it. Content that supports this need could include:

  • Demo or tutorial content;
  • Onboarding videos;
  • Training emails for new customers;
  • Checklist PDFs.

Here’s a sample onboarding email from Asana that recommends three specific activities as starting points to help new users quickly realize the program’s value:

Getting customers to the first moment of value may not be content’s primary job. It might take more hand-holding (as in cases where personalized onboarding is necessary) to get them over the hump. 

But even in these cases, opportunities likely exist to set expectations for new customers via pre-purchase blog, web, or video content. Think through your current onboarding process and look for places to add clarity or instruction through content.

15. What are the biggest mistakes new customers make when using your product or service?

On a related note, have you ever signed up for a new product or service, made a mistake using it, and then immediately regretted your purchase—even if the mistake was clearly the result of user error? 

Your new customers are going to make mistakes. When they do, they’re going to get frustrated. Shorten their learning curve by developing content that preemptively solves potential problems and deploying it when customers are most likely to face issues.

Depending on the analytics solutions you have in place, you may be able to trigger a message when user engagement measurements suggest they’re encountering problems (such as not logging into an app for three days within a week of purchase). 

In the absence of these solutions, you can make educated guesses based on feedback from your sales, marketing, and customer service teams. If you have a sense of which mistakes customers are likely to make—and when they’re likely to make them—content can turn a frustrating experience into a positive outcome, benefiting you and your customer.

Conclusion

Despite its length, this article isn’t intended to be comprehensive. There are plenty of other ways to generate new ideas and myriad other content formats for deploying them that may be appropriate based on your marketing and business goals

Regardless of how you approach the process, taking the following steps will reveal a wealth of new content ideas, as well as where they should fall in terms of execution prioritization:

  1. Identify your company’s most pressing needs and the corresponding marketing or business metrics associated with them.
  2. Map these metrics to the appropriate funnel stages, as well as the content types most commonly used to support them.
  3. Use the questions in the sections above to generate new ideas specific to your chosen funnel stages. If you already have ideas, prioritize your list according to target funnel stage and the resources required to execute each idea.
  4. Evaluate the performance of content you’ve created using this process at least quarterly, ensuring that some effort is allocated to each funnel stage that’s relevant to your overall sales process.
  5. Make an ongoing effort to capture not just new ideas, but new prompts you think of or encounter that’ll help further fuel your future brainstorming sessions. 

The post 30+ Killer New Content Ideas in 30 Minutes (and How to Prioritize Them) appeared first on CXL.

Machine Learning for Paid Ads: Best Practices in a New Era

Digital advertising relies on serving the right ad to the right audience in real time. The better we get at that, the better we do—that’s the industry mantra, and for a reason. We’ve witnessed vast improvements in the volume and accuracy of customer data, and worked in increasingly sophisticated ad platforms.  Machine learning and AI […]

The post Machine Learning for Paid Ads: Best Practices in a New Era appeared first on CXL.

Digital advertising relies on serving the right ad to the right audience in real time. The better we get at that, the better we do—that’s the industry mantra, and for a reason.

We’ve witnessed vast improvements in the volume and accuracy of customer data, and worked in increasingly sophisticated ad platforms. 

Machine learning and AI improve the ability to recognize patterns and pull the right responses from a database. Anyone who doesn’t learn to use the AI features of ad platforms now will be left behind. Many already have been. 

This means rethinking attitudes, habits, and methods—sometimes profoundly. It ushers in a new era of best practices.

While the space is still evolving, we’ve been in it for a while. These are four keys to take advantage of platforms’ machine-learning capabilities in your campaigns.

1. Use an AI-friendly structure.

In the past, advertisers focused on granularity. “We can account for every penny of spend and show provable ROI”—that was the aim. Now, that same highly granular structure actually limits campaign success.

We have to strike a new balance:

balance of paid account granularity to support ai.

On one side, we have the traditional rewards of higher granularity: higher quality/relevance scores, better insights, and so on. We still want these, but the route we take to them has changed because we’re no longer doing the heavy lifting.

Instead, we’re teaching an AI system to deliver these results for us. All major ad platforms—especially Google and Facebook—use AI to target ads, manage bidding, and budgeting and, increasingly, to optimize creative. To do that quickly and at scale, we often need to sacrifice some granularity. That gives us a data set that can train the AI system faster. 

When the balance is struck correctly, results improve drastically—the AI system is more responsive and attentive to data than a human could ever be. What we lose in granularity we make up for in overall accuracy and effectiveness.

Having said that, we still want enough granularity to get some signals about what’s working and what’s not. Selecting destinations is not what AI excels at—we still need to do that. 

Take Facebook. Back in 2017, Facebook recommended a highly granular approach:

what campaign setup looked like for paid accounts in 2017.

By 2019, things looked very different—fewer campaigns, fewer ad sets:

facebook campaign structure today.

The rationale for this contraction in ad campaigns and sets—this granularity shrinkage—is that the goal has shifted from “control every penny of spend ourselves” to “rapidly train the AI.”

In the learning phase of AI implementation, you see performance drops of ~30%.  Many of the gains we once enjoyed from granularity are eaten at the expense of training the AI. It’s crucial to reduce the duration of this learning phase, which is when you endure the worst performance.

It’s gut-churning to wait it out. But exerting more control (via enhanced granularity) only constricts the incoming data and prolongs the learning phase.

Typically, this updated approach does yield better results. Initially, however, we found it extremely counterintuitive and had to run many experiments to be convinced of its effectiveness.

How does it look outside Facebook? We do our own visualizations, which I’ll introduce to make my point. The size of each box represents spend; color represents ROI—red is bad, blue is good. 

If you’d like to see your ad spend visualized this way, check out our free health check app. You can see how your spend looks and what you can do to improve.

What you see in this visualization is a hyper-granular (SKAG) campaign structure in which a small campaign size seems to correlate with poor ROI (lots of small red boxes). The person who crafted this campaign clearly wanted maximum control.

But they’re not getting enough data from smaller campaigns to optimize them in a meaningful way. They’re probably telling themselves that this is by design—that it’s part of a “portfolio management” strategy in which you accept lower performance from a (large) number of campaigns but balance that with higher returns from other areas. It sounds good in principle (and actually used to work that way). 

The problem? This isn’t a machine learning–friendly structure. The extreme granularity, in many cases, doesn’t just prolong the learning phase but keeps AI from ever leaving it. With so many variables, the system gets stuck in the learning phase, with profitability forever out of reach.

In fact, over 50% of the ad groups in this visualization had not earned a click in three months but were actively running. Of the remaining 50%, most got no more than five clicks across the same three-month time window—and showed no prospects for growth.

Consolidating spend in areas with a large ROI—and pulling the plug on thousands of tiny, go-nowhere ads—makes sense, with or without AI. But it’s also far better to sacrifice some gains from increased granularity and instead focus on getting the AI to full efficacy faster. 

We restructured that campaign to maximize the efficacy for AI, and you can see the difference:

There are still a few smaller ad groups. This isn’t just three big fields. It’s a continuum—not maximum or minimum granularity with nothing in between. But axing thousands of minute, ineffective ads that were impossible to manage trained the AI much faster.

What’s crucial is the degree of granularity in the top 70% of spend volume, which you can see if we stack these two charts on top of each other:

SKAG vs. machine learning structure for ads.

The area outlined in yellow in the top image contains just under 300 ad sets; the one below, 23. Removing low performers from the top 70% led to a radical increase in overall performance.

2. Optimize for the right metrics.

The practical necessities, as well as the advantages, of machine learning have changed how we think about the metrics we optimize for. One of the challenges here is, again, to find the correct balance. 

This time, we’re trying to balance funnel depth with data volume. We need enough data to give the algorithm something to learn on and optimize against, but we also want to be as far down the funnel as possible. 

traditional sales funnel.

However your “funnel” actually functions—most look like maps of some kind of futuristic metro more than a linear funnel—it’s wider at the top. 

Across industries, the conversion rate from MQL to SQL is between 0.9% and 31.0%. Conversion from SQL to customer averages around 22%. But even these sharp bottlenecks pale in comparison to the top of the funnel. The top Google Ads accounts have conversion rates of 11.45%, but the median conversion rate is 2.35%.

The result? We have many more data points at the top of the funnel, so it’s easier to train the AI on that bigger data set. However, success there is not only less valuable but potentially misleading. You can be winning on paper and losing in real life if you’re optimizing for the wrong metric. And TOFU metrics like lead volume or CPL can often be the wrong metrics. 

Here’s what we’ve learned trying to find the right balance. A client had been optimizing for CPL/lead volume, shooting for max lead numbers with a $50 per lead cap. We were getting good results.

We were also getting a clear view of which leads were worth buying and which weren’t. We had some leads that were nice leads (i.e. head terms in our space) but too expensive—$100 each in some cases. Why would we spring for those when we had tons of great leads that were $50 or less?

Then, we switched to a metric a couple of steps deeper into the funnel and started optimizing for SQLs. Here are the before-and-after stacked bar charts, with each color area representing a keyword theme:

before and after ad performance based on tracking sqls.

Our low-cost leads that were a “great” value weren’t converting at a worthwhile rate—they were about 40% overpriced. Higher-cost leads were becoming lower-cost SQLs; they paradoxically both cost more money and were cheaper. We maxed those out and saw a sharp increase in profitability.

This insight changed how we allocated spend. SQL volume increased nicely even though lead volume dropped in some cases. That’s hard for some clients to accept at first, but given the choice between more leads and more qualified leads, they opted for the latter. 

We never would’ve seen this without optimizing to that lower-funnel metric, but we still wouldn’t have seen it if we weren’t measuring and correlating across the funnel. Measure and optimize multiple metrics, multiple interconnected customer behaviors and actions—not just one. Feeding information from down-funnel to higher-funnel helps targeting, so the leads are better quality to begin with.

Tracking multiple metrics also gives you greater accuracy in the same way that triangulating on distant objects tells you new information, like distance and elevation. Track two, three, five customer data points, and you develop new insights. This isn’t possible without AI because of the enormous number of calculations involved, of course.

Correlating deeper conversion data back to campaign data is a technical challenge, so we’re about to get super geeky with this. Here’s how it’s done with Google:

flow chart for offline conversion tracking.

You patch through the Google Click ID (gclid), let’s say, to your CRM, and record it in the customer database associated with that lead. Then, you feed it back into Google when you’re making ad buy decisions, letting you see which creative, audience, geography, and other variables improve deep-funnel metrics. 

But what happens if you switch from optimizing one metric to another? How does your AI implementation manage a new goal?

Managing your AI implementation when KPIs change

What’s weird about this is that it’s a process you kind of feel your way through. When we talk about data-driven marketing, “feel” isn’t a verb you normally hear. But this really is a process of feeling your way to the right outcome. We think of it as “riding the AI beast,” which is a very different and often more intuitive process than “engineering the best ROI.” 

Here are a couple of examples. A client wanted to move from optimizing for a top-of-funnel button click to a middle-of-funnel sign-up. We changed the optimization metric in Google and Facebook—and had a very different experience across the two ad platforms.

We’re not saying which is which so as not to offend anyone. And we’ve seen wonky results on both. The point isn’t that one platform is better than the other. The point is that you need to be prepared for unexpected outcomes when dealing with AI. 

Here’s the first ad platform:

change in cost per click on a platform after ai implementation.

All we did was flip the switch. We told the AI, “Stop doing that, and start doing this,” and you can see where that happened. Lead volume spiked while CPL dropped. Easy! 

Which is cool—when it works. But it doesn’t always come out that way. Here’s the same project, same parameters, but different ad platform:

ai struggling to adjust to changes in ad spend.

This is what it looks like when you can’t just flip the switch. In weeks four and five and, then, in weeks eight and nine, we changed target bids and budgets to boost volume.

However, the algorithm didn’t have the right signals to meet the new bids and budgets, so it simply dropped the volume to almost zero.  We tried a bunch of different things until we finally found a combination that let the algorithm function efficiently.

We were riding the beast here, and this likely will be your experience at least some of the time, too. 

3. Let AI determine the creative fit.

Is this really a wise idea? We’re not necessarily talking about letting AI actually do creative, but we can use it to fit creative to the audience, sometimes in innovative ways. Let’s run through some examples, starting with responsive search ads.

If you’re not running responsive search ads, I urge you to reconsider—this is where the whole space is going. Google and Facebook already match the ad to the customer automatically. There’s no such thing as a “winning ad” anymore. 

When you attempt to manipulate the algorithm to produce a traditional winning ad, you undermine overall performance, sometimes drastically. Even if you manage to produce a winning ad, you have no control over whether it’s shown—the platform makes that decision based on the audience and buyer journey stage.

If you’re not experienced with responsive ads, they work like this: You write pieces of an ad, and then the algorithm assembles them, matching each piece to the audience. 

machine learning-driven ad creation.

You can wind up with thousands of variations. It doesn’t make sense to have one definitive combination—a winning ad, as we used to think of it. Here’s how that looks in action on Google Ads:

dynamic ad creation.

Same keyword, same advertiser, same campaign, but two different recipients at two different stages of the buyer journey. That means different ads.

This lets us step back from trying to figure out every tiny detail and refocus on strategic messaging. That can and should still be tested and based on data, we just don’t need to track small-scale, tactical stuff so much.

The downside is that we lose some control. I don’t get a clear beat on the ROI of specific ads, and, obviously, I don’t get a single winning ad. Instead, I get this:

responsive search ad combinations.

So I come out of these campaigns with a feel for overall performance but not the granular insights we’ve come to expect, which circles back to our need to relinquish some control to get this technology to work for us.

The upside is that you can really improve your quality scores. And we’re finding that you can access additional inventory that wasn’t available before with discrete ads.

Here’s what we saw in this case:

responsive ad performance.

Those are giant, not incremental, changes. Assuming you’re doing the basics properly, those kinds of wins are hard to come by with traditional expanded text ads. But with AI steering creative fit, they’re what you should expect.

Responsive ads tend to optimize mostly to CTR, and there’s still no really great way to test them, but they have a positive impact on quality score if you add them to each ad group, and they’re worth using in and of themselves. 

Here’s how I recommend getting the best out of them:

  • Use drafts and experiments to test variables.
  • Add additional responsive search ads in each ad group.
  • Use the combinations report to identify segments driving the most and least impressions.
  • Remember that responsive search ads recombine and serve ad elements in real time, so you’ll never be able to put together a true apples-to-apples comparison.
  • Don’t forget to use the ad strength indicator as a baseline.
responsive ad combinations.

4. Follow general guidelines for AI in advertising.

Whatever the specifics of your campaigns, goals, and tools, some rules are broadly true. That’s because they’re dictated by the nature of the available technology and the wider landscape—we don’t have a lot of choice about them.

StructureKeep all match types together, except in extreme cases where volume permits separation. Structure campaigns in a machine learning–friendly way with enough conversions per ad set for the algorithm to learn quickly—ideally 50 per ad group per week on Google, 10 per ad group per week on Facebook.
MeasurementOptimize for the right metric, one lower in the funnel but with enough volume.
CreativeUse machine learning to reach the right customer with the right ad at the right time. Write different messages to address different phases of the buyer journey.
AudiencesIncrease audience size. Increase the lookalike audience percentage from 1–5% to 5–15%. Where interest and behavior targets significantly overlap, combine them. Use exclusions to minimize audience overlap.

Conclusion

Putting AI to work in advertising means handing off to machines the tasks that they can do better than we ever could. When it comes to multivariate pattern recognition, machines are already significantly superior to humans.

If you want to match ad elements to the customer journey—or you want to drive radical improvements in CTR and lead price by optimizing for lower-funnel metrics—machines should absolutely be your first choice. 

But when we do this, we can’t just give machines part of the job we’re already doing and then carry on as normal. A car is a lot faster than walking, but you have to build a road for it to drive on; machines do this stuff faster and better than we do, but we have to facilitate that work.

There are tasks that machines are either absolutely terrible at or can’t do at all. A machine can mix pre-existing content into novel combinations based on set criteria; it can’t come up with something new. We’re a long way from push-button marketing.

This is the start—of using machine learning for digital advertising, of exploring a wide-open field, and of establishing best practices to guide our industry’s future.

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