Cressive DX is at the forefront of digital marketing and 2025 brings a new wave of challenges that businesses must tackle. 2024 was a year dominated by the rise of consumer AI tools and their promise to impact all walks of life. Many of our clients have questioned how these disruptive technologies will impact their marketing functions. 

From evolving customer journeys to technological shifts, we believe staying competitive requires a strategic shift. In this article, we’re sharing the top five issues facing digital marketers in 2025 and how we’re helping our clients prepare for them.

1. The Impact of Google AI Overviews on Search

The Challenge

AI Overview (AIO) on Google has shifted how users interact with search results by providing immediate answers at the top of the SERP. While Google had a rocky start with AI Overviews, continuous optimisation has meant that AIOs are now more accurate, especially with factual answers.

This can reduce top-of-funnel or awareness clicks to websites. Businesses that drive traffic to their websites through awareness based content such as guides, how-tos, recipes, etc. would likely see a reduction in response to queries like “What’s trending in fall fashion?” for a fashion retailer or “How to make pour-over coffee” for a nice coffee roaster.

We present key insights from a 4,000 keyword experiment we conducted on AIOs here.

Why It Matters

• Altered Funnel Performance: AIO can highlight your site mid-funnel but you may have to work harder (and invest more) to attract top-of-funnel prospects. This impacts your marketing ROI and revenue growth.
• Reduced Organic Traffic and Leads: AIO may overshadow your traditional listings, leading to fewer awareness-stage clicks and potentially reducing your sales pipeline.
• Lost Visibility at Critical Stages: If your site isn’t cited by AIO, you risk being absent from early consideration. This can lower brand awareness and limit future conversions.

How you can adapt to AI Overviews

• Refine content strategy: Write comprehensive, machine-readable explanations. Structure text like Q&A formats or step-by-step guides so AIO can easily parse and cite.
• Optimize for AIO: Similar to Featured Snippet optimization, use concise, highlight-ready segments alongside schema markup.
• Track AIO performance: Monitor how often your content surfaces in AI Overviews, adapting content and SEO tactics accordingly. Governance precedes performance here.
• Assess multi-stage funnel: Measure where users come from (AIO vs. organic listing vs. other channels) and how they move down the funnel.

A tool like DX Spotlight will help you keep track of your organic and overall search performance as well as your ownership of AI Overviews with respect to competitors.

2. Attribution in a Non-Linear Funnel

The Challenge

Modern buyer journeys zigzag across multiple platforms—Reddit, Spotify, social media, and more—making it difficult to isolate which channel truly drives conversions. Not understanding the ‘Place’ component of the marketing mix is a key fundamental issue to address.

This challenge is especially pronounced for B2C brands, where consumers might see an influencer’s Instagram reel, hear a mention on a podcast, and finally run a branded Google search before buying. Without robust cross-channel tracking, it’s easy to attribute the sale solely to organic search, ignoring the earlier touchpoints.

Why It Matters

• Inconsistent Brand Management: Fragmented insights make it harder to ensure consistent branding and messaging, which dilute brand equity and weaken customer trust.
• Inefficient Budget Allocation: Incomplete attribution can lead to overspending on underperforming channels or neglecting high-impact ones, directly affecting marketing ROI.
• Missed Revenue Opportunities: When conversion paths remain hidden, you risk underinvesting in key platforms where customers actually convert, leading to lost sales.

How you can manage the non-linearity

• Cross-platform tracking: Tag all campaigns, set up platform pixels (e.g., Facebook, LinkedIn, Pinterest), and centralize data to see cohesive user journeys.
• Adjust KPIs: Create metrics aligned to each platform’s user intent and funnel stage.
• Automate data capture: Use AI-driven analytics and workflow tools to gather, analyse, and visualize data from multiple sources.
• Channel-specific content: Tailor content for each channel (e.g., short Q&As for Reddit, audio-friendly content for podcasts, etc.).

3. The Bot Crisis in Analytics

The Challenge

Bot traffic is growing ever more sophisticated, often accounting for a significant amount of traffic. Cressive’s own research matches this report by Thales, putting bot traffic close to to 50%.

Brand and presence websites can encounter large spikes in traffic metrics as well as behavioural events such as scrolls and pageviews. Some sectors are particularly susceptible. Ecommerce, travel, hospitality sector businesses may see bots testing booking engines or filling forms, distorting performance metrics across various geographic domains.  

In both scenarios, analytics become skewed, ROI calculations suffer, and marketing decisions risk being guided by false signals.

Why it Matters

• Inaccurate KPIs and Poor Decision-Making: Contaminated data can misdirect marketing strategies, causing wasted spend on irrelevant audiences.
  
• Unclear ROI: Bot-driven conversions inflate results, masking the true performance of campaigns and causing you to over- or underspend in certain channels.
  
• Potential Security Risks: Malicious bots may exploit vulnerabilities, risking brand damage, revenue loss, or additional mitigation costs.

How you can ‘Rehumanize’ Web Analytics

• Firewalls and filters: First-line defences (bot-blocking, IP filtering) offer partial solutions but can’t block all advanced bots. They can be expensive and ineffective.
  
• Enhanced GA4 filtering: Implement custom segments, IP exclusions, and detect suspicious patterns (e.g., unusual bounce rates, improbable geolocation clusters). It’s time consuming and ineffective playing whack-a-mole with exclusions.
  
• AI-based detection: Tools like DX Spotlight which uses AI to identify non-human activity on your websites, effectively ‘rehumanizing’ analytics to enable confident decision-making. We cover humanize in detail in our detailed blog article.

See DX Spotlight Humanize in action below:

4. Cookie Consent Compliance

The Challenge

Stringent data privacy regulations (GDPR, CCPA, etc.) require explicit user consent for tracking, leading many visitors to opt out. Striking a balance between legal compliance and retaining actionable analytics is an ongoing struggle for digital marketers of all sizes. 

For instance, an e-commerce site, which relies heavily on a single website for all sales and marketing, might lose visibility into half of its user base when those visitors decline cookies.

However, the problem is far more complex for many of our clients, which are multi-site organizations operating across multiple regions. Due to different compliance requirements across regions, these organizations have to implement several variations of consent banners, resulting in a fragmented compliance picture with inconsistent data outcomes.

Why it Matters

• Reduced Data for Analysis: If a significant number of users opt out, your analytics may provide an incomplete picture, leading to suboptimal campaign strategies and wasted budget.
  
• Hindered User Experience: Poorly managed consent banners can frustrate visitors, causing them to abandon your site, directly affecting sales and customer loyalty.
  
• Legal and Financial Exposure: Fines can reach up to 4% of global revenue for serious compliance breaches, which can cripple marketing budgets and harm your reputation.

Possible Solutions

• First-party data strategies: Encourage logins (e.g., membership, loyalty programs), so users willingly share data for personalized experiences.
  
• Enhanced analytics for opted-in users: Focus on higher-quality data subsets. Expand understanding with server logs or name server data.
  
• User-centric design: Make cookie pop-ups transparent and user-friendly, explaining the benefits of consenting to non-essential cookies (e.g., better product recommendations)
  
• Automated compliance governance: A tool like DX Spotlight helps monitor consent management, ensuring you stay compliant while gathering relevant insights.

5 Migration/site changes such as CMS change

The Challenge

Overhauling a website—whether merging domains for a global manufacturing conglomerate or switching the CMS for a boutique travel agency—carries high risk. Migrations that overlook SEO best practices can trigger indexing issues, broken redirects, and duplicate content. 

Even for a single-site business, minor missteps in URL structures or metadata can result in immediate visibility loss, jeopardizing revenue until SEO and technical fixes are implemented.

In a larger organization with multiple sites, the complexity multiplies thereby increasing risk. It’s therefore more likely to miss critical details that cause traffic drops across entire regions.

Why It Matters

• Immediate Traffic and Revenue Loss: A poorly planned migration can lead to a steep drop in organic visibility, directly impacting e-commerce sales or lead generation.
  
• Extended Recovery Period: If rankings plummet, it can take months to reclaim your position, leading to prolonged dips in revenue and higher make-good costs.
  
• Stifled Future Growth: Choosing the wrong platform or neglecting SEO considerations can hamper your ability to scale, wasting ongoing marketing spend and undermining long-term business objectives.

How to Migrate Better

• Integrate SEO from Day One:
  • DO involve SEO teams early to map old URLs, plan redirects, and avoid “SEO afterthought” scenarios.
  • DO NOT assume a new CMS is fully optimized out of the box.
    
• Adopt a Marketing- and Customer-Centric Approach: DO recognize that migrations affect user experience, brand perception, and revenue—not just back-end systems.
  
• Establish a Comprehensive Data Baseline: DO benchmark key metrics (rankings, traffic, conversions) before making changes so you can accurately measure post-migration results.
  
• Plan for Ongoing Measurement and Auditing: DO automate rank tracking and on-page audits before, during, and after launch to quickly catch and address any issues.
  
• Contact Cressive DX and discuss your options: info@cressive.com

Detailed Methodology & Stats

1. Data Collection & Sample
   • 4,000 queries total: 2,000 each in the US and UK.
   • Queries were classified by funnel stage, keyword length, and question vs. non-question.
2. AIO Incidence & Word Count
   • We recorded whether an AIO appeared and measured its word count if it did.
   • Sub-analyses split results by region, funnel stage, question format, and keyword length.
3. Citations
   • For each AIO, we noted whether it cited organic positions 1–10, and how many total sources it included.
4. Statistical Tests
   • We employed Kruskal-Wallis for comparing median word counts across multiple groups.
   • We used Z-statistics and McNemar’s tests to compare proportions (e.g., top 3 vs. positions 4–7, 1–7 vs. 8–10).
   • Significant differences suggest we can be confident the patterns (e.g., citation rates) are not due to random chance.

The post 5 Top Issues Facing Digital Marketing and SEO in 2025 appeared first on Cressive DX.

Bot traffic now accounts for nearly 50% of all web traffic and is growing more sophisticated each year, making traditional analytics data unreliable for business decisions. While existing solutions struggle to address this challenge, DX Spotlight’s AI-powered Traffic Classification module identifies and filters out non-human traffic, restoring the human perspective to your analytics data.

Bot Traffic Today

For over a decade, web analytics served as a reliable compass for understanding digital customer behaviour. But that reality has fundamentally shifted. Today, your analytics are probably lying to you – and increasingly sophisticated bots are the culprits.

A staggering 50% of all internet traffic now comes from bots, with malicious/ bad bots alone accounting for 32% in 2023 (source). For businesses tracking their digital presence, this means one in two ‘visitors’ might not be human at all.

Types of Bot Traffic: Breaking Down the Numbers

Legitimate Bots (18% of total traffic):

• Search engine crawlers indexing content e.g. Googlebot, Bingbot, GPTBot
• Analytics and monitoring bots e.g. UptimeRobot, ArchiveBot
• Social media crawlers e.g. Facebookexternalhit, PinterestBot 

Malicious Bots (32% of total traffic):

• Traffic manipulation bots: Artificially inflate website metrics
• Web scrapers: Systematically copy data and content
• Ad fraud bots: Click on paid advertisements or on fake ads.
• Account takeover bots: Target login endpoints to gain unauthorized access

The Rising Challenge of Bot Detection

Traditional bot blocking is becoming increasingly ineffective. Modern bad bots don’t just conceal obvious automated markers – they actively mimic human behavior patterns. These bots have evolved to create traffic patterns nearly indistinguishable from legitimate users. 

Cressive DX’s analysis of client data regularly uncovers logically impossible patterns in raw analytics data – like pages being viewed without any corresponding sessions. These anomalies exist regardless of whether organizations use Google Analytics, Adobe Analytics, Matomo or other solutions, and so are increasingly more than a factor of the recording systems themselves.

When Numbers Lie: The Real Impact on Analytics

The current level of Bot infestation in analytics data makes analysis nigh impossible. One of our clients, a B2B SaaS brand, noticed a large spike in all traffic metrics during February 2024. The marketing team initially – optimistically – attributed this to their seasonal campaign. However, analysis revealed that 90% of this traffic came from sophisticated bad bots, making the campaign’s true impact unclear.

Another client saw pageviews rise up dramatically while sessions increased by 100%. The initial assumption was that their product campaign and updated internal linking structure were paying off. The reality? Bad bots were copying product information, creating artificial pageview inflation while maintaining somewhat realistic session counts.

These examples highlight a critical problem for digital brands: when bot traffic contaminates analytics data, it doesn’t just skew numbers – it fundamentally undermines the ability to make informed decisions. Marketing budgets risk getting misallocated chasing phantom engagement. Content strategies optimize for bots rather than humans. Most concerningly, brands lose sight of genuine customer behaviour patterns, making it impossible to improve real user experience and drive authentic growth.

“The impact is a critical for digital brands: bot traffic contaminates analytics data and it fundamentally undermines analysis” 

Some Markers of Bot Traffic for Self Diagnosis

While sophisticated bad bot traffic is difficult to quantify and adjust for, there are some markers in analytics data that can be used to ascertain their presence, using your analytics source. This analysis is best carried out over a month or longer period.

1. Traffic anomalies: Spikes in sessions and/or pageviews that are substantially higher than average traffic for the period.
2. Traffic from multiple unexpected locations on the same day.
3. Very high or very low bounce rates.
4. 1, 2 and/or 3 above combined with direct or undefined channels.

The Inadequacy of Existing Solutions

Most available solutions for managing bot traffic focus on prevention – blocking bots before they can access your website. While this approach seems logical, it faces several fundamental challenges:

Prevention vs Reality

• Standard advice typically includes:
• Installing firewalls e.g. Azure WAF
• Configuring robots.txt files
• Blocking suspicious IP addresses
• Customizing analytics platforms
• Implementing cloud-based protection services e.g. Cloudflare

While these measures can help reduce bot traffic, they face a fundamental problem: public websites need to remain accessible. Complete bot prevention is nearly impossible without severely impacting legitimate users.

“Blocking based solutions miss a critical point: public websites need to be accessible”  

Analytics Platform Limitations

Analytics platforms like Google Analytics 4 have built-in options to counter bot traffic:

• IP/host blacklisting
• Referral exclusion lists
• Built-in bot filtering
• Custom filters and segments

However, these tools rely on identifying known patterns. Modern bots constantly evolve their behaviour, making static filtering rules increasingly ineffective. Moreover, managing these filters becomes a resource-intensive task with diminishing returns.

The Missing Piece

Perhaps most importantly, traditional solutions don’t address a critical question: What happens when bots inevitably make it through? For businesses trying to understand their true customer engagement, blocking some bots isn’t enough – they need to identify and filter out non-human traffic from their analytics data. 

Traditional solutions don’t address a critical question: What happens when bots inevitably make it through?

Humanizing Analytics through DX Spotlight

Our Analytics Classification module, part of DX Spotlight, directly addresses this challenge. Rather than attempting to block bots – a strategy that often fails against sophisticated automation – the solution focuses on using AI to identify and filter out non-human traffic from analytics data. The module is currently in beta and undergoing continuous R&D, but the results already speak for themselves.

Looking at the B2B SaaS brand example from earlier, the difference between raw traffic (sessions and pageviews) and actual human traffic as determined by DX Spotlight is striking. While raw analytics showed a dramatic spike in sessions, the filtered data reveals a much more stable pattern of genuine user engagement. This clean, bot-free view of traffic provides the reliable foundation that brands need for data-driven decision making.

How DX Spotlight Traffic Classification Works

1. Data Ingestion and ETL: Data collection from any mainstream analytics source.
2. Pattern Analysis and Classification: ML-based classification pipeline
3. Reporting: Reporting Human Traffic on DX Spotlight.

Benefits for Brand Owners

With Bot Traffic identified and most importantly, quantified, Spotlight enables analysis of clean, human analytics data.

DX Spotlight even adjusts and provides human-only traffic across key dimensions such as channels, locations, devices and more.

Having human-only data makes strategic month-by-month planning meaningful, for example through our Bowler report that tracks our clients’ Governance and Site Performance progress based on monthly targets.

Your Analytics, Humanized through DX Spotlight

Clean analytics isn’t just about better numbers – it’s about understanding real customer behavior in a landscape where bots increasingly blur the line between automated and human traffic.

With DX Spotlight’s Traffic Classification module, brands finally see their digital presence through a clear lens: human traffic only.

Discover how much bot traffic is actually affecting your analytics and marketing decisions – schedule a demonstration today.

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