Behind those millions of searches, clicks, saves, and sign-ups are real signals that show exactly what audiences care about and how they engage. For example, retail sites saw a 693% surge in traffic tied to AI-powered shopping assistants and chatbots this year. That kind of growth suggests shoppers are becoming more comfortable letting AI do the comparison shopping for them. Buy now, pay later also became an even more popular option, implying that shoppers were looking for ways to make bigger purchases feel manageable.

January is your opportunity to harness those insights or let them languish. This guide looks back at what worked during the holidays and how to use those insights to plan more effectively for 2026 and beyond.

What People Searched for in December (and Why It Matters Now)

December queries are shaped by the year people just lived through. Sometimes, they signal indulgence; other times, restraint.

Google’s Holiday 100 trends, for instance, made a few patterns clear. In 2025, search interest clustered around practical gift categories: things like movie projectors, weighted vests, kids’ scooters, and backpacks. At scale, that mix suggests steady demand for items that solve everyday needs and feel worth the spend.

In addition to category interest shifts, broader consumer behavior illuminated how people actually made decisions across the season:

• AI-driven sales in the U.S. topped $3 billion on Black Friday alone
• Conversion rates from AI referrals outpaced traditional social channels by a wide margin
• Value-seeking and sharply price-conscious shoppers favored smaller-ticket gifts
• A majority of consumers said rising prices would influence their holiday spending, especially among younger generations facing tighter budgets

Taken together, these signals point to shoppers who were deliberate, price-aware, and increasingly influenced by tools that helped them feel confident about their choices.

In terms of actionable insights here that can carry over to 2026, focus on what reduced friction for people when decisions got complicated. Look at Google Trends and see how searches like “budget gifts” stack up against “luxury gifts” in your market. Then pull last Q4’s Search Console data to see what actually brought people in, not just what you assumed would. Saves on social and interactions with short-form or AI-generated clips tend to spike when people are narrowing choices.

The throughline: Context beats cleverness. When money feels tight, “under $25 gifts” will outperform premium roundups almost every time. For 2026 content planning purposes, marketers should prioritize formats that answer real questions and make next steps obvious.

Where Specificity Wins

Holiday SEO moved fast. January is when you can finally see what held up in search and what didn’t. Rankings have settled, traffic has normalized, and it’s clearer which pages earned their visibility versus which ones were buried.

Looking back, many Q4 search wins came from specificity. Gift-giving phrases, problem-driven queries, and local intent tended to outperform broad holiday terms. Pages that spoke directly to last-minute or highly specific needs earned traction, while generic “Christmas” pages faced steeper competition and more mixed intent.

Long-tail targeting is likely to become even more useful as more discovery happens through conversational queries, whether people type them, speak them, or ask an assistant. In many categories, those behaviors create whitespace brands can capture with clearer, more specific pages.

There’s a particular opportunity with voice search that most businesses are still missing, as we can see below:

Before deciding what to update or reuse next year, check how competitive your keywords were and whether your site was realistically positioned to rank. SEO checkers are useful for validating where effort paid off and where it probably never had a chance.

A post-holiday SEO review usually surfaces takeaways like:

• Holiday URLs that performed well are worth keeping live and updating each season
• Structured data helped certain pages stand out in crowded results
• Updated pages outperformed brand-new ones
• Page speed and simple layouts mattered during high-intent searches
• Basic accessibility improvements supported engagement

Use what December showed you to make cleaner, more realistic SEO decisions going forward.

Building a Content Calendar That Works in January

If December reveals which content holds up under pressure, January is the time to translate those signals into structure. Use the month to reset your publishing rhythm around the pieces that consistently supported real decisions.

A few best practices:

• Publish anchor content early so it can build momentum over time (guides, evergreen explainers, core resources).
• Create decision-support content that aligns with key moments when people are choosing quickly.
• Craft audience-specific pieces tailored to distinct segments instead of broad, one-size-fits-all topics.
• Make space for short-cycle content that moves from idea to publish quickly during spikes.
• Focus on low-friction formats that reduce cognitive load and help people progress without extra steps.

Leaving roughly 20% of the schedule open creates space to respond to demand as it appears, while keeping the rest of the plan stable.

Turning Holiday Insights Into Your Next Plan

The holiday season has passed, and what remains is the record: what people clicked, saved, returned to, and ignored when their attention was stretched thin.

Start with what you already know. Pull the last two years of Q4 data and identify five things that consistently worked. Build around those wins. Add one new experiment to keep learning and to give yourself room to improve.

Momentum comes from simple steps taken in order. Choose one tactic from this guide and implement it today. Tomorrow, choose another. Progress stacks quickly when the next step is always clear.

Audiences respond to clarity. Content that helps them decide, solve something practical, or move forward with less friction earns trust over time. Keep doing that consistently, and your strategy keeps paying dividends, season after season.

Ready to see which stories actually move people through the funnel? Contently’s platform surfaces performance signals across search, social, and conversions — all in one place. See how it works.

Frequently Asked Questions (FAQs):

What’s the biggest lesson marketers should take from the 2025 holiday season?

That audiences reward clarity. Content that helps people compare options, feel confident, and move forward tends to outperform splashy, generic pieces — especially when budgets feel tight.

What metrics matter most when analyzing post-holiday performance?

Look beyond traffic. Prioritize assisted conversions, time on key decision pages, return visits, saves, and email sign-ups. These signals reveal which pieces reduced friction and moved people closer to a decision.

What should I prioritize in January when planning my calendar?

Build around what worked. Anchor evergreen guides early, schedule decision-support content around key moments, leave ~20% of your calendar open for flexibility, and use short-cycle formats when urgency spikes.

The post What’s Working in Content for 2026? What the Holiday Season Taught Us appeared first on Contently.

That’s because there’s still a gap between AI’s promise and its practical value — you know, all those “AI best practices” that no one can quite trace back to real outcomes. Meanwhile, clicks and organic traffic are in freefall.

Of course, at Contently we firmly believe in the value of AI as a force multiplier for great teams. Used thoughtfully, it can streamline research, tighten workflows, and help people ship higher-quality content faster.

But we also recognize that there are some persistent “marketing myths” about what AI can realistically do for content programs and how to use it effectively. These myths tend to take root because AI marketing advice swings between extremes: Hype merchants promise transformation without effort, while skeptics dismiss everything as a fad. Neither helps the marketing director trying to figure out what actually works on Monday morning.

This is the year to get that clarity. Here are five myths that deserve to stay in 2025.

Myth 1: More AI Tools Automatically Mean More Efficiency

On paper, it sounds logical: Add more AI, get more done. In practice, it often works the other way around: Instead of replacing manual steps, many teams end up layering tools on top of one another.

The takeaway isn’t “use fewer tools,” but rather that true efficiency comes from connected workflows. When AI lives inside the places work already happens — your briefs, your CMS, your editorial calendars — the gains start to show up. Good training and clear guidelines can also do more for productivity than chasing the newest feature set.

What works: Before adding anything new, map your current process end to end. Look for bottlenecks AI can realistically remove, consolidate where possible, and invest in helping your team use the tools they already have with confidence. Some basic guardrails also keep everyone from experimenting in five different directions at once.

Myth 2: AI Content Performs Just as Well on Its Own

Thanks to AI, we’re no longer short on content. Most teams can publish more than ever. The real challenge is creating work that actually sounds like you — and earns more trust than the nearly identical post your audience saw five minutes earlier.

Performance now hinges on expertise and perspective, not volume. Search engines and readers both look for signals that someone who knows the topic is actually behind the keyboard, but generic AI text often lacks the lived experience and perspective that makes content persuasive. In other words, grammatically correct copy isn’t the same thing as a compelling narrative.

What’s more, left to its own devices, AI tends to default to the safest version of an idea, which is rarely memorable (and probably won’t drive conversions).

The teams seeing results are treating the AI content creation process as a collaboration. They layer in examples from real customers, clarify claims, tighten arguments, fact-check (!!!), and make sure every piece serves a clear business goal.

What works: Use AI to speed research, outlines, and first passes. Then layer in human editing for accuracy, voice, story, and differentiation.

Myth 3: AI Will Solve Bad Strategy

AI optimizes execution. But it cannot fix fuzzy positioning or off-base business goals. Speed amplifies direction, including the wrong direction.

We see this play out all the time. Teams use AI to publish more, faster… and the metrics that matter don’t budge. Traffic goes up, but conversions stall. The content ranks for keywords, but it doesn’t speak to real buyer pain. Without clear positioning or a path to conversion, all that new visibility simply evaporates before it reaches pipeline.

What works: Get crisp on messaging and conversion paths before you scale production. Then let AI help you execute a strategy that’s already pointed in the right direction.

Myth 4: Everyone Needs to Adopt AI for Everything Immediately

FOMO drives bad technology decisions. Teams adopt tools because competitors are using them, not because they actually solve identified problems. Those wrong-fit tools then create cost, confusion, and cynicism that makes future adoption harder.

The teams that make AI work may not move the fastest, but they do make those moves deliberately. They start by identifying a problem worth solving, define what success should look like, and only then pick the technology.

Readiness also matters. A team still ironing out basic content workflows won’t get much leverage from advanced optimization features. A team without clear governance can accidentally multiply brand, legal, and data-privacy risks as soon as AI scales production.

What works: Look for a single, high-impact use case where AI can remove friction or cost. Run a contained pilot. Document what improved (and what didn’t). Expand from there.

Myth 5: AI Search Is Basically the Same as SEO

Marketers understand visibility through rankings. So it’s easy to assume AI-powered answers are just another extension of Google’s algorithm. They aren’t.

Traditional SEO metrics like site structure and performance remain foundational. But AI Search works differently. Instead of ranking pages, language models compress and rewrite information across multiple sources. According to Ahrefs’ 2025 research, AI Overviews reduce clicks to top-ranking pages by 34.5%. In short, ranking well no longer guarantees visibility.

Visibility in AI Search depends on whether your content is structured clearly and rich with credible context. Two articles might rank identically on page one. The one with clear structure, schema markup, and direct answers gets cited repeatedly by AI assistants. The other rarely appears in AI-generated responses.

What works: Maintain traditional SEO foundations while adding practices designed for AI visibility — clear entity definitions, structured data, and question-driven content formats.

If the last few years were about experimentation, the next one should be about discipline. Use AI where it helps, skip it where it doesn’t, and focus on outcomes instead of promises.

Here’s to a 2026 with fewer breathless predictions and more proof that the work is actually working.

Ready to build AI workflows that actually help your team accomplish real work? Contently’s AI-assisted content platform combines generative AI efficiency with editorial oversight — so your team accelerates without sacrificing quality or brand safety.

Frequently Asked Questions (FAQs):

How do I know if my team is ready for AI adoption?

Assess your current content operations first. If your team has documented workflows, clear brand guidelines, and consistent publishing processes, you’re ready to pilot AI tools. If basic operations still feel chaotic, strengthen those foundations before adding AI complexity.

What’s the minimum investment needed to see results from AI?

Most teams can start with existing tools. Many content platforms now include AI features at no additional cost. The real investment is time: Expect to spend two to four weeks training your team on effective prompting and editing workflows before seeing consistent productivity gains. Budget for those learning curves.

How should I balance traditional SEO with AI Search optimization?

Treat them as complementary. Continue building topical authority, improving site performance, and earning quality backlinks — these fundamentals still matter. Layer AI-specific practices on top: structured data markup, clear entity definitions, and content formats that answer questions directly.

The post 5 AI Marketing Myths to Leave Behind in 2025 appeared first on Contently.