Flat Traffic, No Budget: What Ziff Davis’ Jonathan Berthold Tests First

Your traffic is flat, and you don't have a budget to throw at the problem. What should you test first?

And how do you get your boss to approve an experiment when you can't promise it will work? I put those questions to Jonathan Berthold, VP of Revenue at Ziff Davis, on The Search Engine Journal podcast.

Start With A Site Analysis, Then Target Bottom Of Funnel Content

When traffic is flat and there's no budget, Jonathan starts with a full site analysis to find out why traffic stalled. He has inherited sites in that condition before, ranging from B2C SaaS companies to informational lead generation sites. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate.

The risk is usually hidden in the execution layer. A page can look fine to a human and still fail for an automated visitor if the form, call to action, rendering path, or confirmation step is not accessible enough for the agent to complete the task.

Get Buy In By Defining What You Will Learn

Jonathan sees approval as a communication problem. He never tells a leader that the team will test something and hope for a result. Every experiment is an opportunity to learn. He starts with a hypothesis, and the pitch explains what the. The practical question is what this changes in the system: the page structure, the evidence presented, the measurement habit, or the way the topic is connected to related work.

The practical value is in connecting the idea to an observable signal. That means deciding what should be checked, what would prove the issue is real, and where the team should make the smallest useful improvement first.

Start Small So One Test Can't Tank The Site

I raised a concern about the quick fixes circulating now that newcomers are using to enter SEO through AEO and GEO. Those tactics work until the algorithm catches up. I'd rather keep experiments contained than put an entire website at. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate.

Give SEO Time, And Set A Different Rule For Paid Media

When a test isn't going the way you hoped, when should you stop? Years ago, the standard advice was to give an SEO test six to nine months, especially for a new site, but iterations move much faster now. I asked Jonathan how he decides. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate.

The useful check is whether this improves the system behind search performance, not only the words on the page. Internal links, crawlable content, clear entities, current evidence, and a sensible page structure all help the recommendation become easier to trust.

The Test Most Marketers Skip Happens After The Click

Jonathan sees the same gap in SEO and paid media. Marketers put nearly all their attention on generating traffic and overlook "what happens when a user actually hits your website." Any page that already draws a lot of organic traffic, or. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate. This connects with Is Google Fixing B2B Marketing? when the same signal needs a clearer operating decision. The same pattern also shows up in LLM Traffic Converts Differently, where the practical question is how the signal becomes visible.

Use Citation Data To Find Outreach Opportunities

Jonathan is also running his own experiment that connects bottom of funnel targeting with link building. He uses AI citation data "to unearth link building opportunities." He sees it as a way to spot where LLMs are heading and to build. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

Use Intent To Choose Keywords When Search Volume Is Low

Jonathan no longer puts much stock in search volume. Search habits change every day. If the context and topic are right, a long tail keyword can still be worth targeting even when Google, Moz or another platform reports it at one, 10 or. The measurement question is whether this signal changes a decision, not whether it adds another number to a dashboard. Useful reporting connects visibility, engagement, and business outcomes without pretending every AI influenced journey will produce a clean click path.

The reporting question is whether this signal changes a decision. If it only creates another number in a dashboard, it adds noise. If it helps separate profile activity, website visits, calls, bookings, and direction requests, it can make local performance easier to understand.

Test Where the Revenue Is

As AI answers absorb informational searches, Jonathan says focus on high intent searches, even when the volume is low. He also recommends running tests on the pages where visitors decide whether to convert. A small test in those places can. The search implication is whether the section improves the evidence around the page, not simply whether it adds more wording. Clear entities, crawlable structure, internal links, and useful context are what make the topic easier to evaluate.

Start With A Site Analysis, Then Target Bottom Of Funnel Content in practice

Introduction Your traffic is flat, and you don't have a budget to throw at the problem. What should you test first? And how do you get your boss to approve an experiment when you can't promise it will work? I put those questions to. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

What the visibility signal actually changes

What the visibility signal actually changes: flat Traffic, No Budget: What Ziff Davis’ Jonathan Berthold Tests First: the Practical Angle should be treated as a visibility signal, not a standalone headline. Introduction Your traffic is flat, and you don't have a budget to throw at the problem. What should you test first? And how do you get your boss to approve an experiment when you can't promise it will work? I put those questions to Jonathan Berthold, VP of. A useful companion note is 000x Human Traffic in 5 Years, because it looks at a nearby part of the same system.

What the visibility signal actually changes: the practical question is whether the page, brand evidence, and surrounding content make the answer easier to trust. If that support is weak, search systems can still understand the topic but fail to connect it confidently to the brand.

What the visibility signal actually changes: that is why the response should begin with an audit of the evidence already on the site before creating a new asset. The fastest improvement is often a clearer page, a better internal link, or a stronger explanation of why the brand belongs in the answer.

Where the evidence needs to be tested

Where the evidence needs to be tested: a single study or ranking observation should not become a strategy by itself. It should become a diagnostic prompt: which source is being trusted, which query pattern is affected, and which part of the site would make that trust easier to earn?

Where the evidence needs to be tested: that keeps the response grounded. The goal is to improve the evidence chain around the topic rather than publish another summary that repeats what every other page already says.

Where the evidence needs to be tested: the important distinction is between a useful signal and a fashionable talking point. A useful signal changes the brief, the page structure, the linking plan, or the measurement view.