In Part 1 of our series, we introduced Share of Voice (SOV) as a critical metric for understanding your brand’s digital market presence. Now, let’s dive deeper into how this powerful metric is calculated and why it provides insights that simpler metrics simply can’t match.

The Science Behind SOV Calculation

Let’s look at how our DX Studio data platform calculates Share of Voice in practice through a systematic five-step process:

1. Data Collection

First, we gather search data for your target keywords by:

• Identifying keywords that define your market
• Collecting SERP data across these keywords
• Capturing both your brand’s and competitors’ positions

Our experience shows that 250-1000 keywords provide the optimal balance for statistical significance, depending on your sector.

2. Position Analysis

We analyze the raw position data to understand:

• Your brand’s placement in search results
• Position changes over time
• Competitor presence for your target keywords
• Position distribution across keyword groups (awareness, consideration, action)

3. Traffic Estimation

To estimate potential traffic value, we combine:

• Search volume data
• Position-based CTR models
• Search features that affect CTR

This transforms position data into visibility and potential traffic estimations.

4. Share Calculation

We calculate market share by combining position and traffic data across all competing brands, expressing your brand’s portion as a percentage of the total market. This gives us your Share of Voice – the percentage of potential search visibility belonging to your brand.

5. Monthly Aggregation and Reporting

Daily data is aggregated and reported monthly using DX Spotlight to provide:

• Stable metrics that smooth daily fluctuations
• Period-over-period comparisons
• Progress tracking against targets and competitors

What makes this metric particularly powerful is its ability to account for both the quality of your positions (through CTR curves) and the quantity of potential traffic (through search volume data). This combination provides a much more accurate picture of market presence than simpler metrics like average position or keyword rankings alone.

SOV in Action: A Real-World Example

Let’s dive into a real-world example that demonstrates how Share of Voice translates into actionable insights. Looking at one of our client performance charts, we can see significant growth in both Position Score and SOV over time:

A detailed analysis of position ownership across keyword categories reveals:

Key insights from the data:

• Increased Top 3 positions across all stages driving SOV growth
• Strong dominance in awareness stage (47.1% of Top 3 positions)
• Weaker presence in action stage despite recent gains
• Concentrated growth in high-CTR top positions
• Only 30% of consideration and 25% of action keywords owned by tracked competitors, revealing unidentified market players

The month-over-month improvements might seem incremental, but they represent significant gains in market visibility when you consider:

• The competitive nature of these positions
• The high search volume associated with these terms
• The compounding effect of improvements across different keyword groups

Short-Term vs. Long-Term Value of SOV

The example above demonstrates the immediate value of SOV in tracking and improving digital performance. While this client is already seeing tangible benefits, the real power of SOV lies in both its short-term insights and long-term predictive capabilities.

As seen in our research and echoed by experts like Les Binet, SOV delivers value across multiple time horizons:

Short-Term Benefits:

1. SEO Focus and Prioritization
   • Forces assessment and pragmatic prioritization of SEO factors
   • Drives focus on the most valuable keywords based on search volume
   • Encourages consideration of click-through rates, not just rankings
2. Competitor Intelligence
   • Reveals competitors you didn’t know you had in search
   • Provides insights into competitive strategies
   • Measures the whole sector, not just a few pre-selected competitors
3. Brand Visibility Insights
   • Spotlights opportunities to improve brand visibility
   • Identifies weaknesses relative to competitors
   • Provides a list of actionable improvements
4. Organizational Capabilities
   • Helps CMOs inform search strategy direction
   • Enables tracking of consumer demand
   • Provides a framework for reporting progress to stakeholders

As Richard Game captures here, these immediate benefits make SOV valuable even before its long-term impact on market share is realised.

In our final instalment, we’ll show how to transform SOV insights into strategic action and reveal how leading brands use this metric to drive sustainable growth.

To learn more about how Cressive DX can help you measure and improve your brand’s Share of Voice, contact our team for a personalised demonstration of our DX Spotlight platform.

The post The Science Behind Share of Voice: How It’s Measured and Why It Matters appeared first on Cressive DX.

Ah, the joy. The moment when you pull up your monthly performance dashboard and see those trend lines heading in the right direction. A rare point of agreement for both client and consultant. That steady climb in Search Performance KPIs isn’t just a validation of the underlying strategy; it’s a clear signal that your brand is gaining ground in the digital battlefield.

But what exactly are we looking at here, and why does it matter so much for a digital Brand?

Understanding Search Performance: The Digital Battleground

In a digital-first world, your brand’s search performance is arguably its most critical competitive advantage. Think about it – when was the last time you, or anyone you know, made a significant purchase decision without consulting Google? Search performance represents your brand’s ability to be present and prominent when potential customers are looking for solutions you provide.

But what exactly constitutes search performance? At its core, it’s your brand’s visibility and ranking in search engines compared to your competitors across the keywords that matter in your market. It’s not just about ranking well for a few terms – it’s about dominating the digital conversation in your industry.

Ranking position equates to being found, being ‘in the game’, to be seen by prospective customers at the top of the search funnel.

Share of Voice vs Position Score: The Two Pillars of Search Performance

At Cressive DX, we summarize search performance through two high-level KPIs: Position Score and Share of Voice (SOV). While both are important, they serve different purposes and provide different insights.

Position Score is the simpler of the two metrics. It provides a straightforward summary of your SERP (Search Engine Results Page) positions across all your target keywords.

For instance – from the below chart (which our tech team calls the “position tube map”) Cressive ranks No. 1 for the keyword Digital Brand Governance in March 2025.

Each keyword has similar daily position data that we collect, which when averaged out over all keywords and a period of time leads to Position Score. Think of it as your brand’s average ranking report card. It’s useful because:

• It gives you a quick snapshot of your overall ranking health
• It’s easy to understand and communicate to stakeholders
• It helps track basic SEO progress over time

But Share of Voice? That’s where things get really interesting.

Share of Voice goes beyond simple rankings to tell a more powerful story. While Position Score tells you where you rank, SOV reveals how much of the market you actually own by measuring your brand’s share of the digital conversation. It’s a sophisticated metric that analyses your visibility across search results, weighted by search volume and click-through rates. It takes into account:

• The actual search volume for each keyword
• The click-through rates at different positions
• Your competitors’ presence and rankings
• Both organic and paid search results
• The relative importance of different keywords in your market

This complexity makes SOV a more accurate representation of your brand’s true digital market presence and potential impact, relative to your competition. As referenced in multiple contributors on shareofvoice.com, SOV has historically been one of the most reliable predictors of market share growth, and in the digital age, this relationship has become even more pronounced.

Furthermore, as we cover here, a focus on Share of Voice/ Share of Search delivers value to the business in the short term.

The Market Dimensions of Share of Voice

Understanding Share of Voice requires thinking about your digital market in three key dimensions:

• the search terms people use when engaging with your market i.e. keywords
• the platforms where these conversations happen
• and the geographic location of your audience.

Let’s break this down.

The Keyword Dimension: Defining Your Market Space

Your market isn’t just about what you sell – it’s about the entire conversation surrounding your industry. Think of keywords as the language your potential customers use when they’re in your market space. This language can be understood through two complementary lenses:

First, looking at user intent:

• Problem Space Keywords: Terms people use when trying to understand or solve a problem (e.g., “how to gain muscle mass”)
• Solution Space Keywords: Terms related to specific solutions or product categories (e.g., “whey protein powder”)

Second, considering the buyer’s journey:

• Awareness Stage: Broad industry terms and educational queries (e.g., “what causes hair loss”)
• Consideration Stage: Comparison and evaluation terms (e.g., “minoxidil vs finasteride”)
• Conversion Stage: Purchase-intent keywords (e.g., “buy hair loss treatment online”)

Importantly, your market definition specifically excludes brand-specific terms (like your company name or product names). Why? Because brand searches don’t represent market share – they represent brand awareness. To truly understand your competitive position, you need to focus on non-branded searches where you’re competing for new customers. This becomes even more critical in the era of Google’s AI Overviews which are changing search behaviour, especially at the top of the funnel.

The Platform Dimension: Where the Conversations Happen

While Google remains the dominant player in search, the digital landscape has evolved significantly, especially post-2020. Here’s how the platform dimension breaks down:

• Google Organic and Paid: Still accounts for the majority of website traffic and remains the primary battlefield for digital visibility
• Social Media: Brands generally have a strong presence across Facebook, Instagram, Twitter, LinkedIn in order to expand their audience and build engagement
• Community-based Platforms: These include the likes of Quora and Reddit
• eCommerce: Organic and Paid positions in Amazon are critical for consumer products

As discussed in our Top 5 DM issues for 2025 article, we know the customer journey is becoming more non-linear and ‘across channel’ so data capture of these platforms and attribution to each of them is key to understanding the complete picture.

The Location Dimension

Geographic location of the searcher is also an important dimension as search results are localised and are becoming more so. This dimension is more important to search engine platforms rather than social media and community-based platforms.

In our next article (Part 2 of the series), we’ll dive deeper into how Share of Voice is calculated and analyse a real-world example that demonstrates its impact on digital performance. We’ll explore the science behind the metric and reveal how leading brands are using it to drive measurable growth.

To learn more about how Cressive DX can help you measure and improve your brand’s Share of Voice, contact our team for a personalised demonstration of our DX Spotlight platform.

The post Understanding Share of Voice: The Digital Brand’s North Star Metric appeared first on Cressive DX.

Google’s AI Overviews (AIO)—the generative summaries sometimes appearing at the top of search results—are creating new opportunities and challenges for SEO. They provide quick, synthesised answers, often citing multiple organic pages. For marketers, AIOs can potentially reduce clicks on traditional organic links while also spotlighting the websites Google trusts most.

As we cover in our analysis of the top issues facing digital marketing in 2025, we believe AIOs will cause substantial disruption to search marketing in the months and years to come.

To understand how AIOs work “in the wild,” our team analysed 4,000 search queries (2,000 each from the US and the UK). These queries covered awareness, consideration, and conversion keywords as well as question vs. non-question formats and short-tail, medium-tail, and long-tail variants. The analysis was carried out on 23rd January 2025.

Below, we share our 10 biggest takeaways.

Note: For those who want to dive into statistical significance tests (e.g., Kruskal-Wallis, Z-statistics, McNemar’s test), check out the Detailed Methodology & Stats at the end.

1. AIOs Appear for Almost Half of Searches

Across the full range of search terms, 47% triggered an AI Overview while 53% did not. In other words, you’ve got nearly a 50-50 chance of seeing an AI Overview for a given query.

As Google refines its generative approach, this rate may well increase—making it crucial to understand how (and why) AIOs surface.

2. Minimal Geographic Differences: US vs. UK

Breaking down the same dataset by location, we see a 46.63% incidence for the UK and 47.76% for the US. Given how closely these figures align, it appears that Google’s AIO rollout is similarly advanced in both markets.

If you’re ranking for queries in either region, anticipate a comparable chance of generating an AI Overview.

3. Question-Based Queries Are Far More Likely to Yield AIOs

One of the standout findings involves query intent:

Question-format keywords: ~85% show an AIO

Non-question keywords: ~43% show an AIO

If your audience tends to type “How do I…?” or “What is…?”, these types of queries are extremely likely to trigger an AIO.

4. Funnel Stage Influences AIO Appearance

We classified each query as awareness, consideration, or conversion. Here’s how often each stage displayed an AI Overview:

• Awareness: ~56% AIO incidence
• Consideration: ~23%
• Conversion: ~42%

5. Long-Tail Keywords Trigger AIOs Most Frequently

Next, we grouped queries into short-tail, medium-tail, and long-tail:

• Long-tail: ~65% include an AIO
• Medium-tail: ~49%
• Short-tail: ~34%

Specific, more detailed queries tend to invite more thorough AI Overviews—likely because Google sees a stronger need to synthesize multiple sources for these narrower topics.

6. The Nuanced Story of AIO Length

We also looked at the word count of AI Overviews based on funnel stage, keyword length, and whether it was a question or not.

Although these differences are statistically significant, the real-world impact may be relatively small. For example, consideration queries produce slightly longer overviews, but this could also be due to the complexity of the topic rather than the funnel stage itself.

In other words, AIO length is not driven exclusively by these factors—they’re just part of the picture. Content complexity and Google’s available data likely play a bigger role in shaping final word counts.

7. Nearly All AIOs Cite the Top 10 Organic Results

If you’re wondering whether organic rankings still matter when an AI is rewriting the SERP, the answer is a resounding yes. We found:

• 97.3% of AIOs cited at least one result from the top 10 organic listings.
• Only 2.7% didn’t cite any top 10 result.

8. The Two-Tier Citation Pattern: Positions 1–7 vs. 8–10

Digging deeper, we discovered a sharp divide in citation rates:

• Positions 1–7: ~83–85% citation rate
• Positions 8–10: ~56% citation rate

Our statistical tests show no meaningful difference between the top 3 positions and positions 4-7.

However, there’s a highly significant drop from positions 1–7 to positions 8–10. If you want to influence the AI Overview, aim to be within the top 7. After that point, citation rates plummet.

9. Number of Citations: More About Availability than Keyword Type

We also measured how many sources are typically cited in an AIO.

While the averages for awareness, consideration, conversion, and different keyword lengths varied (e.g., ~5–6 citations), the data suggests these slight differences don’t strongly correlate with the funnel stage or keyword type.

Instead, the number of citations appears to be driven by how much topically relevant content Google deems credible and already ranks highly. In other words, Google’s AI pulls from however many high-ranking pages it believes best serve the user query—so the richer the existing pool of quality and relevant content, the more citations you’ll see.

10 . Why Top Organic Results Are the Bedrock of AIO

One of our most compelling discoveries is also the most logical: AI Overviews essentially stand on the shoulders of Google’s ranking algorithms. Consider the following:

1. World-Class Relevance: Google has spent decades perfecting how to rank content. It’s far more efficient for them to build AI Overviews using the top-ranked pages than to re-invent the relevance engine from scratch.
2. Consistency vs. Contradiction: The AI Overview typically aligns with the consensus of top results. If an AIO were to contradict the highest-ranked sources, it would raise questions about whether the AI is incorrect or Google’s rankings are flawed. Either scenario undermines user trust.

For brands, this means SEO fundamentals still matter—perhaps more than ever. If you can get into (and stay in) the top 7 organic positions, you stand a much higher chance of:

• Being front and centre when an AI Overview appears.
• Shaping the narrative around a topic

Conclusions & Next Steps

The bottom line is that AI Overviews rely on the top organic results for both content and credibility. While AIOs may feel like a shortcut for users, relevance and authority remain rooted in Google’s ranking algorithms. With nearly half of all queries we examined triggering an AIO, your best strategy is to:

• Continue optimizing for Page 1, especially the top 7 positions.
• Craft comprehensive, relevant content that serves user intent (particularly for question-based queries)
• Monitor funnel-stage performance and adapt content strategy for awareness vs. consideration vs. conversion.

Generative AI may shift how users consume information on the SERP, but it doesn’t replace the fundamental importance of ranking highly for competitive keywords.

Detailed Methodology & Stats

1. Data Collection & Sample
   • 4,000 queries total: 2,000 each in the US and UK. Selected as indicative of client behaviour modelled over buying funnel.
   • 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 10 Essential Insights From Our Google AI Overviews Study 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.

The post Beyond Basic Bot Detection: Humanizing Web Analytics through DX Spotlight appeared first on Cressive DX.

In the digital analytics world, the transition from Universal Analytics (UA) to Google Analytics (GA4) marked one of the significant events of the year and it is pivotal for any enterprise focusing on Digital Brand Governance and enhancing their Share of Voice.

While UA, with its session-based tracking system, has been an essential web data analysis tool for years, GA4 introduces a more dynamic and event-based approach. This offers a big shift on how data is collected and interpreted.  And now, UA has been phased out, leaving us with GA4. This begs the question: What’s next? How do GA4 and UA differ, and what are the challenges of this transition?

Some Differences Between GA4 and UA 

One of the fundamental differences lies in the tracking approach: UA’s session-based approach provided a linear view of user interactions, while GA4 with its event-based tracking offers a more granular, user-centric perspective. This change grants a deeper understanding of user behaviour and engagements.

When it comes to data visualisation, UA displayed multiple pre-set charts by default. On the other hand, GA4 works best when integrated with third-party tools like Google’s Looker Studio or the Cressive DX platform for more comprehensive data analysis. GA4 is more exploratory and customisation-based.

Another noteworthy difference is in data retention. GA4 has a reduced data storage duration limited to 14 months in the free version compared to UA and this presents a challenge for long-term data analysis and historical comparisons.  Unlike UA, GA4 also includes specific features such as Streams ID and cross-domain tracking, which offers enhanced capabilities in tracking user journeys across various domains. 

These are only a small portion of distinctions between the two with other differences in areas such as user metrics, pageviews, sessions, and account structure, many of which we are likely already familiar with. But, Google being Google, things aren’t that simple and the transition from UA to GA4 made things more complicated than what it was… 

Issues and Aftermath – What Now? 

GA4 has brought a number of challenges to the table. The shift to event-based tracking forced organisations to reevaluate their existing analytics strategies and possibly retraining of staff. The change wasn’t all sunshine and rainbows for businesses, it was a challenging process where most of them lost valuable historical data and adapting to those changes required a great deal of resources and time.

A few simply switched to other web analytics tools such as Matomo or Adobe Analytics because of GDPR (General Data Protection Regulation) a European Union regulation on information privacy. Countries including Italy, France and Austria have banned Google Analytics on the grounds of violation in data collection and storage practices. 

Furthermore, GA4 relies on third-party tools for data visualisation and analysis. This necessitates partnerships with tool providers and deep understanding of those softwares, impacting both the workflow and the budget. Plus, reduced data retention impacts the importance of timely data analysis and decision making. Embracing GA4 is not just about adaptation: it’s about solid analytics strategies to remain agile in a rapidly changing digital landscape. 

At Cressive DX, we have more than 3 decades of combined experience in guiding enterprises through these difficult transitions: from understanding the core differences between Universal Analytics and Google Analytics 4, to implementing new strategies for Digital Brand Governance and maximising Share of Voice. Using our proprietary software and proven industry expertise, we turn your data into insights and insights into high value solutions, pragmatically and without the fluff. Best-practice brand control leads to better Digital Brand Performance. 

Originally published 1 December 2023 on LinkedIn.

The post GA4 and UA – What’s the Difference? appeared first on Cressive DX.

Intro read, 5min

Share of Search (SoS) is the poster child of digital marketing metrics. Many experienced marketeers rightly sing the praises of SoS as an ingredient of digital marketing, Mark Ritson vocal amongst others. The value of SoS as a predictor of future market share is increasingly accepted, due to the fine recent work of Les Binet.

This value, and model of causation, is commonly understood in the digital age: in the way Google can predict election results from search activity, SoS (and higher search visibility to consumers searching online) can lead to higher market performance over time.

The data behind this argument is in two parts. Firstly, SoS calculated now. Secondly the change in market share measured later. The latter ROI can be assessed when the results are known, but how can such investment in the metrics be justified before, in the present?

As a long term marketing strategy SoS has CMOs licking their lips for future outcomes, but what about results now, for the next quarter, to justify SoS? How does a CMO sell the idea of SoS to the Board to get started?

Here I’ll help explain another business case for digital share of search as a leading KPI in your digital marketing arsenal (leaving the wider conversation of the longer term value, as well as the definition and methods of how to calculate SoS, etc, to other articles).

First, “Where’s the beef?”

As Wendy’s asked in the US and Canada in 1984. (CMOs are hungry, they want fast food.)

SoS has benefits by virtue of the process of calculation itself. It’s valuable to add this to the growing wealth of knowledge in this subject area as the data increases over time. This is based on our own firsthand experience and research in providing Share of Search (SoS), and Share of Voice (SOV), reporting.

Business case in the short term

One of our clients saw consistent value from the operational use of SOS. The data insights from our global digital reporting toolkit recommended a greater focus on SEO factors in one of their regions, and in the 1.5 years period since this focus shift their share of search rose from 5.3% to 7.9%: a 50% improvement. Completely measurable, now, before we talk share.

So how did SEO improve SoS?

SEO benefits from Share of Search

SEO analysis and scrutiny in the short-term force assessment and, importantly, pragmatic prioritisation of the SEO factors that comprise the customer-oriented calculation of SoS.

When considering the scope of target keyword search terms, the number needs to be large enough to resemble the entire market you operate in – where your customer is – but not be too large and bog down analysis. What is the optimal number? An empirical answer is 250-1000 keywords to best define a market sector with reliable statistical significance (dependent on the sector and its nature). Keyword sets larger than prove unwieldy and diminishing returns start (at this point you’re into PPC territory of numbers of keywords. Smaller than this struggles to define the market; in our experience more than 40 terms are needed, which is a fundamental restriction of the Google Trends method of calculation.

A robust and focused definition of the keyword data set better considers the target market and audience definition, and leads to better search strategy.

Next, the value of each keyword is relative in SoS and assessed by monthly search volume, provided by your chosen keyword research tool, Google for instance, to prioritise target terms according to user demand, and qualifies them to your target audience. Ranking matters, but ranking for the most important terms matters more.

SEOs will be familiar with this value above and beyond pure ranking position when they also take click through rate (CTR) into account, and not just ranking position per se. Share of Search forces this qualification to the benefit of the digital marketing process.

Relative position is demanded by SoS. Calculation of your competitors’ SoS is built in – you more often than not find competitors you didn’t know you had in search. The whole sector is measured, using every search result, and this provides valuable competitor intelligence. This is often forgotten within typical SEO reporting tools and not provided by default, Opportunities can be missed if you don’t take a holistic market view.

Consideration of SoS helps define the whole search market. Both organic (/natural) and paid search rankings ideally need inclusion and analysis, with the necessary detailed analysis of both. We’re find untapped value in their overlap, revealing otherwise hidden benefits to search marketing. The market can be scoped wider even to encompass eCommerce (Amazon for instance) in addition to search engines and the same SoS calculated and similar SEO benefits gained. (The details of these covered in another article.)

Ultimately within this wider search context brand visibility – through an SoS lens – verges into the discipline of brand governance, in which SoS is an important metric. This governance of digital is activity another benefit to brand marketing and SEO.

These benefits – macro and micro – can be delivered by a cost-effective repeatable scalable reporting process: a corporate Share of Search solution. They are in addition to the long-term impact on future share of market predicted by SoS.

Why wait until the long term? SoS can benefit your marketing now. So how can CMOs convince the board to invest, now?

Selling Share of Search to the Board

SEOs know the value of the constituent parts of SoS, but what about CMOs? What business benefits resonate with them and help them sell convince their audience the Board?

• Share of search spotlights opportunities where to improve brand visibility and increase awareness of a brand to consumers, whose use of online is now paramount for a brand;

• Weaknesses, absolute and relative to competitors, can be identified and provide a list of what to fix when CMOs delegate search objectives downwards to their Heads of Digital;

• CMOs can more easily inform Search Strategy and direct organisational abilities to chart a correct course over the long term for market share impacts;

• Tracking consumer demand, gaining insights and reporting on progress. CMOs can show business impacts using SOS reports as an organisational capability, in a way not possible with just SEO data.

The ‘C’ level and Board love the idea of a long-term systemic process to drive market share where it can be derived from controllable digital marketing activities. Good CMOs plan long term, but all CMOs need benefits in the short term. They need to show results in order to help the Board to sanction initiatives and keep faith for the long term.

SoS in this equation is an upstream factor relative to the resulting share of market. However, SoS itself is a downstream factor – and as such uncontrollable – when compared to the search activities (upstream search activities and tasks) of SEO: including technical improvement, better content, website standing, backed by the necessary reporting.

Understanding this shorter term value helps CMOs ‘sell’ SoS internally.

They get the double whammy of SoS value now from SEO benefits, and value later from correlated market share: jam today AND jam tomorrow.

ROI from Share of Search

With SoS considered a complex ‘top of the tree’ KPI, its calculation needs to be worth the effort. Modern solutions of automation and presentation make it fast and cost effective.

CMOs left to ponder where to get started can ask their Heads of Digital to commission the correct technology to drive the process, to harness SEO, and to produce SoS as a KPI for their brands. Indeed most organisations are probably already managing many SEO parts of the SoS calculation, but falling short of capitalising on the benefits of SoS as a metric itself.

Organisations can make SoS reporting and benefits a reality by articulating, and appreciating, where to gain value from using SoS as a KPI, and by harnessing the associated SEO processes behind it.

Richard

If this was helpful please share it, or reply to me, I’d like to hear. All my thoughts are shared with a ‘no content for content sake’ pledge. Read more digital marketing articles from me, the Chief Talker at Cressive DX.

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