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Web Team Project Prioritization Frameworks To Set SEO Up For Success

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Web Team Project Prioritization Frameworks To Set SEO Up For Success

Corporate web teams are often overloaded with a combination of one-off change requests and large projects.

Teams are forced to find a balance between requests coming from other stakeholders in the business and their own internal web team initiatives.

This state of affairs can create tremendous unnecessary stress and lead to unnecessary work. It can make it difficult to get the right work accomplished – and that includes SEO-related requests.

In this post, we’ll explore how to deal with this quandary by creating and adhering to a project prioritization framework.

The Difficulties Of Project Prioritization For Web Teams

Most corporate web teams include some combination of Development (developing and maintaining the code and systems), Operations (publishing content and making changes), and Strategy (specialties such as SEO, Analytics, UX, and Content) – along with management.

Web teams are typically in a precarious position in a corporate setting as they’re expected to:

  • Maintain mission-critical infrastructure 24/7/365.
  • Maintain content that may have no stakeholder owner
  • Execute as flawlessly as possible on projects that have executive visibility.
  • Execute on an endless stream of content changes and technical requests from stakeholders around the business – which likely will not have executive visibility so long as they’re completed sufficiently and in a reasonable timeframe.
  • Advance towards improvements in KPIs or OKRs – many of which will be internally driven.

Meanwhile, the team must:

  • Keep things interesting and engaging for the web staff.
  • Improve team morale and unity & not burn people out.
  • Write and maintain documentation & automation scripts in support of all of the other work.
  • Demonstrate the value of the Web team to other teams and top executives.
  • Demonstrate the value of sub-teams and individuals to the Web team leader and their manager.
  • Accurately plan for the right number of humans, with the right set of skills, required to do everything that will be needed in the coming months and years for development, operations, and strategy.
  • Be prepared to pivot to new objectives at any time.

Conflict can arise due to having more requests and committed projects than the team can reasonably handle – or even intake and scope.

Simply adding more team members doesn’t solve the issue (and can even exacerbate it) for a few reasons.

Hiring/onboarding can take months, more management is required for more staff, and discreet projects requiring specific staff or skills might only last a few months (among others).

And this all takes time away from the most effective, skilled, and knowledgeable staff the team already has.

Web teams are in a unique position within a large organization because websites have become not just the front door but the virtual headquarters.

As the world has moved online (and accelerated due to COVID)  more employees working from home still need to be seen as productive.

Corporate web teams have experienced an unprecedented increase in the number of requests to publish new things, make minor edits, and deal with stakeholders.

Many stakeholders view a web team as simply order-takers and not strategic partners.

The options are basically:

  • Take on every request received, with urgency. This necessarily results in an overwhelming volume of work, burnout, and mistakes.
  • An individual on the web team spends much of their time reviewing and arbitrarily deciding on each request – whether to pursue or not and where it fits in the order of priority – and trying to explain to stakeholders why their projects are being delayed or not being worked on.
  • A leadership committee reviews requests on a periodic basis and determines which type to support regularly, which new projects to take on, and in what order.
  • The team develops and sticks to a rubric or framework for decision making and prioritization, which is used to evaluate requests and prioritize among other commitments. If a stakeholder’s request must be delayed or not acted on, the web team can point to the framework for justification.

These aren’t necessarily exclusive of one another – there is no reason a committee can’t also rely on a framework.

Whatever the method is, it’s important to communicate to the entire web team and external stakeholders so they can understand how and why decisions are being made.

Basic Requirements For Balancing Projects

Before your team can prioritize the work they’re going to commit to, there are a few basics to put in place.

These are the guard rails that guide other decisions and actions and help the team set clear boundaries with executives and other teams.

1. Team Charter

Your web team needs to have a charter in place that includes things like the mission statement, the values that are important, and the general goals for the team.

2. Inventory Of Existing Commitments, Services Provided, And Systems Maintained

Consider a working list of the services the team provides to other teams, the systems and processes the Web team is responsible for, and an inventory of the commitments the team has made to executives and other teams in the organization.

3. Scoping Of Potential New Projects

In case there is a backlog of potential projects already, you can accurately scope the projects to include possible timelines, individuals required, cost, etc. which helps with deciding what projects get worked in what order.

4. Support From Leadership

If corporate leaders do not support the Web team’s ability to push back on stakeholder requests or view the Web team as strategic expert partners, then your team has no chance at maintaining the balance between internal Web-driven needs and the flood of requests a Web team receives.

5. Web Team Roadmap

It’s critical to begin plotting out the projects that are expected to occur at different times in the future.

Some projects are recurring, some are done once and never to be done again.

Some projects must happen within a very specific timeframe.

Some projects are incredibly important, but have no critical due date and are thus deprioritized forever.

For the short-term, consider 6-month or 12-month roadmaps with specific projects identified and the expected timeframe for project completion.

Start with the known date-committed projects, like supporting quarterly product launches or an annual event, upgrading the version of a critical system, or migrating to a new technology to avoid losing critical functionality that will be end-of-life’d by a vendor.

For the long-term, it can be helpful to consider very broad goals in a 2- or 3-year timeframe. How do you want the team to be operating that far in the future and how is that different from today?

A Framework For Project Prioritization

The following represents a draft of a framework that can be used to prioritize web team projects and requests.

Think of this as a starting point, but consider what is most important in your organization and with your technology stack – and consider what buckets make the most sense for your team.

Highest

Keeping The Lights On (KTLO) – Addressing production bugs impacting large numbers of users in significant ways and necessary updates to critical systems.

These activities are necessary for everything else on the list and become the very top priority when they occur.

Examples might include:

  • CMS-critical infrastructure updates.
  • Website or section is down with a Status Code 0 or 5XX.
  • Broken links.
  • Other UI on mission-critical web pages.

High

Executive Special Request Projects – Projects that a VP or other top executive is asking for, even if it may not seem likely to move the needle on a stated business-critical KPI.

In practically every organization, the most important thing you can do is support and trust your executives.

In some cases, working on these projects will mean not working on other projects and potentially not hitting some KPIs.

If a trade-off with other work will be required, it’s important to let the executive know what we won’t be doing to act on their request so they can make an informed decision.

The trade-off KPI that you might now be less likely to achieve could become a stretch goal.

Examples might include:

  • Redesigning the homepage.
  • Redesigning site navigation.
  • Developing a microsite.
  • Adding visual bells and whistles.

Business-Critical Projects – These are projects necessary for the business to continue operating.

Typically, these requests support stakeholders outside of the Web team.

A top executive might have visibility into these projects, but it’s not their pet project.

Examples might include: Dealing with acquired websites, product renaming, and launches, fixing analytics for existing reports/use-cases, legal-requested changes, retiring old domains & websites, updating an annual event website, publishing new blog posts, making edits to critical webpages, implementing cookie notices & accessibility standards.

Medium

Web Team Initiated Projects – Projects that advance a Web team towards their business KPIs and “doing the right thing” for the business.

Examples might include: Optimizing for conversion rate, improving user experience for prospects, bringing a website up to speed with competitors for areas like resource centers, improving product or free trial pages, A/B tests, or improving site navigation.

Web Team People Projects – Projects that demonstrate the Web team’s value or improve team culture.

Examples might include: Quarterly on-site/off-site meetings, quarterly meetings with other business units, monthly analytics reporting, all-hands meetings, virtual or in-person coffee, games and team building activities, creating T-Shirts/mugs/swag for the team.

Enabling Projects – Projects that automate or free-up Strategy, Development & Operation time to enable the Web team to have more time for other projects.

Examples might include:

  • Website/domain footprint reduction.
  • Component-izing HTML areas.
  • Automating sitemaps.
  • A redirect management tool.
  • Jira clean-up.
  • Improved processes with other teams.

Low

Non-Critical Bugs – These are problems that need to be fixed, but they might not be impacting business KPIs quite yet.

Examples might include:

  • Production bugs experienced by end-users on minor pages.
  • Fixing analytics issues to enable future reporting use-cases.
  • Improving UI for a subset of device types.

Non-Critical Improvements – These are improvements to the site that needs to happen, but not necessarily immediately.

Examples might include:

  • Eliminating redirect chains.
  • Non-critical A/B testing.
  • Site speed optimization.
  • Non-critical user testing/feedback/surveys.
  • Non-critical bugs not seen by users (such as bugs on internal interfaces or redirects missing analytics tracking).

Other Stakeholder Requests – Projects being requested by others that are not critical for the business or Web team KPIs and that are not advocated for by Executive leadership. Working on these projects can be helpful for improving relationships across teams if there is capacity available.

Depending on your particular team and organization, some of these areas will be a higher or lower priority – or the tasks might be completely different from what is described here.

Assumptions And Other Considerations

To implement a project prioritization framework, certain assumptions are required. Some of these may include:

  • There will always be a large backlog of potential projects. There is always more that can be done to a website, more optimization, more automation, more changes, more maintenance.
  • Not all projects are of equal importance. Some sound good, some are advocated by top executives, some will advance the site or team towards a KPI.
  • Some proposed projects are a bad idea and should not be worked on.
  • A Web team can’t and shouldn’t act on every request they receive.
  • The priorities of the broader team that the Web team reports into – whether marketing, growth, or something else – should guide prioritization and decision making.
  • Data accuracy is paramount when the data is used to justify projects, in prioritization, or to measure success. Thus projects to improve or maintain data accuracy must be elevated to enable prioritization.

Wrapping Up

Web teams simply can’t do everything they want to do, and everything is being asked of them by their stakeholders – including those in SEO.

In order to decide what the team should work on immediately, what to work on eventually (and what requests or projects to never touch), set up a framework.

By setting up a framework for decision making, you’ll avoid the pitfalls of constant arbitrary one-off decision making and help your team stay aligned and motivated to accomplish the most important work for the business.

More resources:


Featured Image: Matej Kastelic/Shutterstock




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Google’s AI Overviews Shake Up Ecommerce Search Visibility

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Google's AI Overviews Shake Up Ecommerce Search Visibility

An analysis of 25,000 ecommerce queries by Bartosz Góralewicz, founder of Onely, reveals the impact of Google’s AI overviews on search visibility for online retailers.

The study found that 16% of eCommerce queries now return an AI overview in search results, accounting for 13% of total search volume in this sector.

Notably, 80% of the sources listed in these AI overviews do not rank organically for the original query.

“Ranking #1-3 gives you only an 8% chance of being a source in AI overviews,” Góralewicz stated.

Shift Toward “Accelerated” Product Experiences

International SEO consultant Aleyda Solis analyzed the disconnect between traditional organic ranking and inclusion in AI overviews.

According to Solis, for product-related queries, Google is prioritizing an “accelerated” approach over summarizing currently ranking pages.

She commented Góralewicz’ findings, stating:

“… rather than providing high level summaries of what’s already ranked organically below, what Google does with e-commerce is “accelerate” the experience by already showcasing what the user would get next.”

Solis explains that for queries where Google previously ranked category pages, reviews, and buying guides, it’s now bypassing this level of results with AI overviews.

Assessing AI Overview Traffic Impact

To help retailers evaluate their exposure, Solis has shared a spreadsheet that analyzes the potential traffic impact of AI overviews.

As Góralewicz notes, this could be an initial rollout, speculating that “Google will expand AI overviews for high-cost queries when enabling ads” based on data showing they are currently excluded for high cost-per-click keywords.

An in-depth report across ecommerce and publishing is expected soon from Góralewicz and Onely, with additional insights into this search trend.

Why SEJ Cares

AI overviews represent a shift in how search visibility is achieved for ecommerce websites.

With most overviews currently pulling product data from non-ranking sources, the traditional connection between organic rankings and search traffic is being disrupted.

Retailers may need to adapt their SEO strategies for this new search environment.

How This Can Benefit You

While unsettling for established brands, AI overviews create new opportunities for retailers to gain visibility without competing for the most commercially valuable keywords.

Ecommerce sites can potentially circumvent traditional ranking barriers by optimizing product data and detail pages for Google’s “accelerated” product displays.

The detailed assessment framework provided by Solis enables merchants to audit their exposure and prioritize optimization needs accordingly.


FAQ

What are the key findings from the analysis of AI overviews & ecommerce queries?

Góralewicz’s analysis of 25,000 ecommerce queries found:

  • 16% of ecommerce queries now return an AI overview in the search results.
  • 80% of the sources listed in these AI overviews do not rank organically for the original query.
  • Ranking positions #1-3 only provides an 8% chance of being a source in AI overviews.

These insights reveal significant shifts in how ecommerce sites need to approach search visibility.

Why are AI overviews pulling product data from non-ranking sources, and what does this mean for retailers?

Google’s AI overviews prioritize “accelerated” experiences over summarizing currently ranked pages for product-related queries.

This shift focuses on showcasing directly what users seek instead of traditional organic results.

For retailers, this means:

  • A need to optimize product pages beyond traditional SEO practices, catering to the data requirements of AI overviews.
  • Opportunities to gain visibility without necessarily holding top organic rankings.
  • Potential to bypass traditional ranking barriers by focusing on enhanced product data integration.

Retailers must adapt quickly to remain competitive in this evolving search environment.

What practical steps can retailers take to evaluate and improve their search visibility in light of AI overview disruptions?

Retailers can take several practical steps to evaluate and improve their search visibility:

  • Utilize the spreadsheet provided by Aleyda Solis to assess the potential traffic impact of AI overviews.
  • Optimize product and detail pages to align with the data and presentation style preferred by AI overviews.
  • Continuously monitor changes and updates to AI overviews, adapting strategies based on new data and trends.

These steps can help retailers navigate the impact of AI overviews and maintain or improve their search visibility.


Featured Image: Marco Lazzarini/Shutterstock



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Google’s AI Overviews Go Viral, Draw Mainstream Media Scrutiny

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Google's AI Overviews Go Viral, Draw Mainstream Media Scrutiny

Google’s rollout of AI-generated overviews in US search results is taking a disastrous turn, with mainstream media outlets like The New York Times, BBC, and CNBC reporting on numerous inaccuracies and bizarre responses.

On social media, users are sharing endless examples of the feature’s nonsensical and sometimes dangerous output.

From recommending non-toxic glue on pizza to suggesting that eating rocks provides nutritional benefits, the blunders would be amusing if they weren’t so alarming.

Mainstream Media Coverage

As reported by The New York Times, Google’s AI overviews struggle with basic facts, claiming that Barack Obama was the first Muslim president of the United States and stating that Andrew Jackson graduated from college in 2005.

These errors undermine trust in Google’s search engine, which more than two billion people rely on for authoritative information worldwide.

Manual Removal & System Refinements

As reported by The Verge, Google is now scrambling to remove the bizarre AI-generated responses and improve its systems manually.

A Google spokesperson confirmed that the company is taking “swift action” to remove problematic responses and using the examples to refine its AI overview feature.

Google’s Rush To AI Integration

The flawed rollout of AI overviews isn’t an isolated incident for Google.

As CNBC notes in its report, Google made several missteps in a rush to integrate AI into its products.

In February, Google was forced to pause its Gemini chatbot after it generated inaccurate images of historical figures and refused to depict white people in most instances.

Before that, the company’s Bard chatbot faced ridicule for sharing incorrect information about outer space, leading to a $100 billion drop in Google’s market value.

Despite these setbacks, industry experts cited by The New York Times suggest that Google has little choice but to continue advancing AI integration to remain competitive.

However, the challenges of taming large language models, which ingest false information and satirical posts, are now more apparent.

The Debate Over AI In Search

The controversy surrounding AI overviews adds fuel to the debate over the risks and limitations of AI.

While the technology holds potential, these missteps remind everyone that more testing is needed before unleashing it on the public.

The BBC notes that Google’s rivals face similar backlash over their attempts to cram more AI tools into their consumer-facing products.

The UK’s data watchdog is investigating Microsoft after it announced a feature that would take continuous screenshots of users’ online activity.

At the same time, actress Scarlett Johansson criticized OpenAI for using a voice likened to her own without permission.

What This Means For Websites & SEO Professionals

Mainstream media coverage of Google’s erroneous AI overviews brings the issue of declining search quality to public attention.

As the company works to address inaccuracies, the incident serves as a cautionary tale for the entire industry.

Important takeaway: Prioritize responsible use of AI technology to ensure the benefits outweigh its risks.



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New Google Search Ads Resemble AI Assistant App

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New Google Search Ads Resemble AI Assistant App

A keynote at Google’s Marketing Live event showed a new AI-powered visual search results that feature advertisements that engage users within the context of an AI-Assisted search, blurring the line between AI-generated search results and advertisements.

Google Lens is a truly helpful app but it becomes unconventional where it blurs the line between an assistant helping users and being led to a shopping cart. This new way of engaging potential customers with AI is so far out there that the presenter doesn’t even call it advertising, he doesn’t even use the word.

Visual Search Traffic Opportunity?

Google’s Group Product Manager Sylvanus Bent, begins the presentation with an overview of the next version of Google Lens visual search that will be useful for surfacing information and for help finding where to buy them.

Sylvanus explained how it will be an opportunity for websites to receive traffic from this new way to search.

“…whether you’re snapping a photo with lens or circling to search something on your social feed, visual search unlocks new ways to explore whatever catches your eye, and we recently announced a newly redesigned results page for Visual search.

Soon, instead of just visual matches, you’ll see a wide range of results, from images to video, web links, and facts about the knowledge graph. It gets people the helpful information they need and creates new opportunities for sites to be discovered.”

It’s hard to say whether or not this will bring search traffic to websites and what the quality of that traffic will be. Will they stick around to read an article? Will they engage with a product review?

Visual Search Results

Sylvanus shares a hypothetical example of someone at an airport baggage claim who falls in like with someone else’s bag. He explains that all the person needs to do is snap a photo of the luggage bag and Google Lens will take them directly to shopping options.

He explains:

“No words, no problem. Just open Lens, take a quick picture and immediately you’ll see options to purchase.

And for the first time, shopping ads will appear at the very top of the results on linked searches, where a business can offer what a consumer is looking for.

This will help them easily purchase something that catches their eye.”

These are image-heavy shopping ads at the top of the search results and as annoying as that may be it’s nowhere near the “next level” advertising that is coming to Google’s search ads where Google presents a paid promotion within the context of an AI Assistant.

Interactive Search Shopping

Sylvanus next describes an AI-powered form advertising that happens directly within search. But he doesn’t call it advertising. He doesn’t even use the word advertising. He suggests this new form of AI search experience is more than offer, saying that, “it’s an experience.”

He’s right to not use the word advertisement because what he describes goes far beyond advertising and blurs the boundaries between search and advertising within the context of AI-powered suggestions, paid suggestions.

Sylvanus explains how this new form of shopping experience works:

“And next, imagine a world where every search ad is more than an offer. It’s an experience. It’s a new way for you to engage more directly with your customers. And we’re exploring search ads with AI powered recommendations across different verticals. So I want to show you an example that’s going live soon and you’ll see even more when we get to shopping.”

He uses the example of someone who needs to store their furniture for a few months and who turns to Google to find short term storage. What he describes is a query for local short term storage that turns into a “dynamic ad experience” that leads the searcher into throwing packing supplies into their shopping cart.

He narrated how it works:

“You search for short term storage and you see an ad for extra space storage. Now you can click into a new dynamic ad experience.

You can select and upload photos of the different rooms in your house, showing how much furniture you have, and then extra space storage with help from Google, AI generates a description of all your belongings for you to verify. You get a recommendation for the right size and type of storage unit and even how much packing supplies you need to get the job done. Then you just go to the website to complete the transaction.

And this is taking the definition of a helpful ad to the next level. It does everything but physically pick up your stuff and move it, and that is cool.”

Step 1: Search For Short Term Storage

1716722762 15 New Google Search Ads Resemble AI Assistant App

The above screenshot shows an advertisement that when clicked takes the user to what looks like an AI-assisted search but is really an interactive advertisement.

Step 2: Upload Photos For “AI Assistance”

1716722762 242 New Google Search Ads Resemble AI Assistant App

The above image is a screenshot of an advertisement that is presented in the context of AI-assisted search.  Masking an advertisement within a different context is the same principal behind an advertorial where an advertisement is hidden in the form of an article. The phrases “Let AI do the heavy lifting” and “AI-powered recommendations” create the context of AI-search that masks the true context of an advertisement.

Step 3: Images Chosen For Uploading

1716722762 187 New Google Search Ads Resemble AI Assistant App

The above screenshot shows how a user uploads an image to the AI-powered advertisement within the context of an AI-powered search app.

The Word “App” Masks That This Is An Ad

Screenshot of interactive advertisement for that identifies itself as an app with the words

Above is a screenshot of how a user uploads a photo to the AI-powered interactive advertisement within the context of a visual search engine, using the word “app” to further the illusion that the user is interacting with an app and not an advertisement.

Upload Process Masks The Advertising Context

Screenshot of interactive advertisement that uses the context of an AI Assistant to mask that this is an advertisement

The phrase “Generative AI is experimental” contributes to the illusion that this is an AI-assisted search.

Step 4: Upload Confirmation

1716722762 395 New Google Search Ads Resemble AI Assistant App

In step 4 the “app” advertisement is for confirming that the AI correctly identified the furniture that needs to be put into storage.

Step 5: AI “Recommendations”

1716722762 588 New Google Search Ads Resemble AI Assistant App

The above screenshot shows “AI recommendations” that look like search results.

The Recommendations Are Ad Units

1716722762 751 New Google Search Ads Resemble AI Assistant App

Those recommendations are actually ad units that when clicked takes the user to the “Extra Space Storage” shopping website.

Step 6: Searcher Visits Advertiser Website

1716722762 929 New Google Search Ads Resemble AI Assistant App

Blurring The Boundaries

What the Google keynote speaker describes is the integration of paid product suggestions into an AI assisted search. This kind of advertising is so far out there that the Googler doesn’t even call it advertising and rightfully so because what this does is blur the line between AI assisted search and advertising. At what point does a helpful AI search become just a platform for using AI to offer paid suggestions?

Watch The Keynote At The 32 Minute Mark

Featured Image by Shutterstock/Ljupco Smokovski

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