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Analytics

ANALYTICS MONTH: Integrating web, CRM and campaign data for a 360° view
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The pressure on marketers to demonstrate return on investment and deliver personalised experiences is higher than ever. The fragmented view of customer data is no longer tenable. Which is why leading marketing teams are attempting to break down silos by integrating web analytics, CRM records, and campaign data into unified analytics platforms. The goal is to enable a holistic, real-time understanding of the full customer journey…

Traditionally, marketing departments relied on disparate tools: Google Analytics for website behaviour, CRM systems for customer profiles and sales pipelines, and third-party campaign tools for channel performance. While each offered valuable insights, the lack of integration meant teams often worked from incomplete or conflicting data sets. Today, unified analytics platforms bridge these gaps, bringing all data sources together to create a single source of truth.

This consolidation enables deeper insights and more strategic decision-making. For example, marketers can now correlate specific website behaviours, such as visits to a product page or abandonment of a cart, with subsequent email engagement and eventual conversion logged in the CRM. Similarly, they can track the performance of a multi-touch campaign across paid social, email, and search channels, adjusting budgets and messaging in real time.

The move toward identity resolution, unifying customer interactions across devices and platforms under a single profile, is another major shift. By consolidating identifiers (e.g. email, cookie, user ID), brands can build more accurate audience segments and deliver personalised content at the right moment, increasing engagement and lifetime value.

Key to this transformation is the rise of customer data platforms (CDPs) and marketing automation tools with native analytics capabilities. Many of these systems now offer AI-driven features such as churn prediction, lead scoring, and dynamic content recommendations based on behaviour across multiple touchpoints.

However, success depends on more than just tools. Marketers must also ensure data governance and compliance, particularly around GDPR, consent tracking, and ethical data usage. A unified view is only valuable if the underlying data is accurate, permissioned, and trusted.

Looking ahead, unified analytics will play a central role in marketing strategy, campaign optimisation, and customer experience design. The ability to view, understand, and act on data from across the funnel, from first click to repeat purchase, is what will differentiate the most agile and effective marketing teams.

It’s time to unify, simplify, and amplify marketing intelligence.

Are you searching for Analytics solutions for your organisation? The Digital Marketing Solutions Summit can help!

Photo by litoon dev on Unsplash

ANALYTICS MONTH: What are the website metrics that matter in 2025?
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For years, bounce rate was a go-to metric for understanding user engagement. But in 2025, bounce rate alone is no longer sufficient, or even particularly useful, for marketers aiming to make data-led decisions in a complex, multichannel environment…

The rise of content-rich landing pages, single-page applications (SPAs), and mobile-first browsing habits has rendered bounce rate increasingly misleading. A user who reads an entire long-form article or interacts with a product configurator, without navigating away, might still count as a ‘bounce’. That’s why forward-thinking marketers are shifting focus to more nuanced engagement signals.

Scroll depth is one such metric. It provides visibility into how far down a user scrolls on a page, offering insight into whether content is actually being consumed. Combined with dwell time (the length of time a user remains on a page before returning to the search results) this paints a more complete picture of content effectiveness and user interest.

Interaction tracking is also taking centre stage. Using modern analytics tools, marketers can now monitor clicks on key page elements (like videos, downloads, accordions, or chat widgets) to understand what drives action. These micro-conversions are becoming more valuable in shaping content strategy and CRO experiments than traditional clickthrough rates alone.

Another rising star in the engagement toolkit is content velocity, which measures how quickly and frequently users consume multiple pieces of content in a single session. This is especially relevant for B2B marketers who rely on resource hubs or thought leadership libraries to build trust and guide buyers through long decision cycles.

Perhaps most importantly in 2025 is the use of intent scoring, an AI-driven composite measure that combines time-on-site, repeat visits, page flow, and behavioural triggers to rank visitors by purchase or lead potential. Intent scoring is rapidly gaining traction in both ecommerce and lead-gen environments, allowing marketers to prioritise remarketing efforts and personalise onsite experiences in real-time.

Adopting these more advanced engagement metrics requires modern analytics platforms, often integrated with CDPs, CRMs, and marketing automation tools, to connect the dots between traffic and outcomes. But the payoff is clear: a more accurate understanding of what users find valuable, what content resonates, and where to invest digital budget next.

Are you searching for Analytics solutions for your organisation? The Digital Marketing Solutions Summit can help!

Photo by Jakub Żerdzicki on Unsplash

ANALYTICS MONTH: Privacy-first analytics and adapting to a cookie-less world
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With the gradual phase-out of third-party cookies and the tightening grip of data privacy regulations, marketers must pivot towards privacy-first analytics strategies…

At the heart of this transformation is the need for brands to maintain audience insights and campaign performance tracking while upholding user consent and data protection obligations. Traditional analytics methods, which heavily relied on third-party cookies for behavioural tracking, are no longer viable. Instead, marketers are embracing a new ecosystem built on trust, transparency, and first-party data.

One of the most prominent changes is the rise of server-side tracking. Unlike client-side cookies, server-side solutions allow brands to control and store data securely on their own servers. This approach not only ensures greater compliance with privacy laws but also improves data accuracy by mitigating the effects of ad blockers and browser restrictions.

In tandem, the use of customer data platforms (CDPs) and consent management platforms (CMPs) has grown exponentially. These tools enable marketers to collect, unify, and activate first-party data across digital touchpoints, while respecting user preferences and opt-ins. CDPs provide the backbone for personalisation and segmentation in a privacy-compliant manner, while CMPs ensure that user consent is clearly recorded and auditable.

Marketers are also rethinking their KPIs and attribution models. Instead of over-relying on clickstream data, many are incorporating aggregate-level insights, probabilistic modelling, and zero-party data, information that users intentionally share, such as preferences and survey responses. This shift requires a cultural change: moving from volume-based metrics to more nuanced, relationship-focused indicators.

Additionally, privacy-first web analytics tools, such as Plausible, Matomo, and Fathom, are gaining traction. These platforms offer GDPR-compliant tracking without storing personally identifiable information or using invasive cookie technologies, making them ideal for brands seeking full transparency with their users.

The transition isn’t without challenges. Data gaps, limited user identifiers, and increased complexity in campaign reporting are common pain points. However, early adopters are finding that privacy-first approaches foster stronger brand trust and improve long-term customer loyalty, an increasingly valuable asset in a crowded digital marketplace.

As we move further into 2025/26, digital marketing leaders will need to balance analytics sophistication with ethical data practices.

Are you searching for Analytics solutions for your organisation? The Digital Marketing Solutions Summit can help!

Photo by Jakub Żerdzicki on Unsplash

July 2025 is Website Analytics Month on Digital Marketing Briefing – Here’s how to get involved
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Each month on Digital Marketing Briefing we’re shining the spotlight on different parts of the marketing sector – and in July we’ll be focussing on Analytics solutions.

It’s all part of our ‘Recommended’ editorial feature, designed to help marketing industry professionals find the best products and services available today.

So, if you specialise in Analytics and would like to be included as part of this exciting new shop window, we’d love to hear from you – for more info, contact Kerry Naumburger on k.naumburger@forumevents.co.uk.

Here’s our features list in full:-

July 2025 – Website Analytics
Aug 2025 – Conversion Rate Optimisation
Sept 2025 – Digital Signage
Oct 2025 – Printing
Nov 2025 – Creative & Design
Dec 2025 – Online Strategy
Jan 2026 – Content Management
Feb 2026 – Lead Generation & Tracking
Mar 2026 – Email Marketing
April 2026 – Digital Printing
May 2026 – Social Media
June 2026 – Brand Monitoring

ANALYTICS MONTH: Make the best data-driven solutions by choosing the best solutions
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Data-driven decision making is paramount. For senior digital marketing professionals, selecting the right analytics solution provider is crucial for gaining valuable insights into audience behaviour, campaign performance, and overall business success. Here’s a guide to help you navigate the market and choose the ideal partner…

Define Your Analytics Needs

  • Identify Key Metrics: Determine the specific data points you need to track, such as website traffic, user behaviour, conversion rates, and customer acquisition costs.
  • Consider Integration: Evaluate the need for integration with existing marketing tools (e.g., CRM, email marketing platforms) for a holistic view of the customer journey.
  • Scalability: Consider your organisation’s growth plans and select a solution that can adapt to increasing data volumes and complexity.

Prioritise Data Accuracy and Reliability

  • Data Quality: Ensure the provider offers robust data collection and processing methods to guarantee data accuracy and reliability.
  • Data Governance: Understand the provider’s data security and privacy practices to protect sensitive customer information.
  • Data Validation: Look for solutions with built-in data validation and cleaning capabilities to minimize errors and inconsistencies.

Evaluate Features and Functionality

  • Advanced Analytics: Seek solutions that offer advanced features like predictive analytics, machine learning, and AI-powered insights for uncovering hidden patterns and trends.
  • Customisation Options: A flexible platform that can be tailored to your specific business needs and industry is essential.
  • User-Friendly Interface: Choose a solution with a user-friendly interface that allows both technical and non-technical users to access and understand data effectively.

Build Strong Partnerships

  • Vendor Reputation: Research the provider’s reputation, experience, and customer reviews to assess their reliability and expertise.
  • Implementation Support: Evaluate the vendor’s ability to provide seamless implementation, training, and ongoing support.
  • Data Ownership: Understand the terms of data ownership and access to ensure you retain control over your valuable insights.

Embrace the Future of Analytics

  • Artificial Intelligence (AI) and Machine Learning: Look for solutions that leverage AI to automate data analysis,identify trends, and generate actionable insights.
  • Customer Data Platform (CDP):: Consider integrating a CDP with your analytics solution for a unified view of customer data across channels.
  • Privacy and Compliance: Stay updated on data privacy regulations (e.g., GDPR) and choose solutions that comply with these standards.

By following these guidelines, senior digital marketing professionals can make informed decisions when selecting analytics solution providers. A trusted partner can empower your organisation to make data-driven decisions, optimise marketing campaigns, and ultimately drive business growth.

Are you searching for Analytics solutions for your organisation? The Digital Marketing Solutions Summit can help!

Photo by Melanie Deziel on Unsplash

ANALYTICS MONTH: Demystifying the maze to create the perfect customer journeys
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Marketers understand the power of data-driven decision making. Website analytics solutions and related services have become indispensable tools, providing invaluable insights into website traffic, user behaviour, and campaign performance. By leveraging these tools, digital marketers can optimise their online strategies, maximise ROI, and ultimately achieve their marketing goals…

The Power of Website Analytics:

  • Understanding Website Traffic: Analytics solutions provide detailed insights into website traffic sources (organic search, social media, paid advertising) and visitor demographics. This data empowers marketers to understand their target audience and tailor their messaging accordingly.
  • Analysing User Behaviour: Website analytics track user behaviour on a granular level, revealing how visitors navigate the website, what content resonates with them, and where potential conversion leaks exist. This allows marketers to identify areas for improvement and enhance the user experience.
  • Measuring Campaign Performance: Analytics platforms enable marketers to track the effectiveness of their marketing campaigns, including website traffic generated, conversion rates, and return on investment (ROI) for individual campaigns. This data allows for data-driven optimisation and budget allocation decisions.
  • A/B Testing and Optimisation: Website analytics tools facilitate A/B testing, allowing marketers to compare different versions of website elements (e.g., call-to-action buttons, product page layouts) and identify what resonates best with users. This data-driven approach ensures continuous website improvement and conversion rate optimisation.

The Evolving Landscape of Website Analytics:

As technology advances and user behaviour continues to shift, website analytics are likely to see some exciting developments:

  • Focus on Artificial Intelligence (AI): AI-powered analytics solutions will become increasingly prevalent. Machine learning algorithms will offer predictive analytics, helping marketers anticipate user behaviour and personalise website experiences for individual visitors.
  • Integration with Customer Relationship Management (CRM): Enhanced integration between website analytics and CRM platforms will allow for a more holistic view of the customer journey. Marketers will be able to connect website behaviour with customer data, enabling targeted marketing campaigns and improved customer engagement.
  • Privacy-Focused Analytics: As data privacy regulations evolve, website analytics solutions will need to adapt.Focus will shift towards collecting first-party data with user consent and utilising privacy-preserving data analytics techniques.
  • Omnichannel Measurement and Attribution: Consumers today interact with brands across multiple channels.Analytics solutions will need to evolve to provide a comprehensive view of the customer journey across all touchpoints, enabling accurate attribution of conversions and campaign effectiveness.

Website analytics solutions have become the cornerstone of digital marketing success in the UK. By leveraging these tools and embracing innovative approaches, digital marketing professionals can gain valuable insights into user behaviour, optimise their online strategies, and ultimately achieve their marketing goals. As technology evolves and the focus on data privacy and user experience intensifies, we can expect website analytics to become even more sophisticated, empowering UK digital marketers to navigate the ever-changing online landscape and deliver exceptional results.

Are you searching for Analytics solutions for your organisation? The Digital Marketing Solutions Summit can help!

Photo by Jakub Żerdzicki on Unsplash

LEAD GENERATION MONTH: Sales analytics held back by data privacy, poor data and limited cross-functional collaboration
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Eighty-four percent of sales leaders agreed that sales analytics has had less influence on sales performance than leadership expected, as indicated by new research.

Gartner surveyed 303 sales leaders in July 2023 to understand the current state of sales analytics and the metrics used to drive insight generation and behavior change within sales functions.

“With analytics comes the expectation of transformative decision making, but the reality is that many organizations struggle to produce actionable insights regarding their most important decisions,” said Kelly Fischbein, Senior Principal, Research in the Gartner Sales Practice.

When asked to identify barriers to analytics success, data privacy concerns or regulations (45% of respondents), poor data quality (44%) and limited cross-functional collaboration (44%) were cited as the top three reasons (see Figure 1).

“The net result is compounding complexity: More uncertainty creates more demand for analytics, which creates demand for more data, which in turn presents analytics teams with challenging operational barriers,” said Fischbein.

Source: Gartner (February 2024)

To address the disconnect regarding sales analytics and influence on sales performance, CSOs must mutually define analytics value proposition with their operations leaders. The Gartner survey went on to find that CSO-led analytics are 2.3 times more likely to achieve higher forecast accuracy than non-CSO led analytics. CSO-led analytics are also 1.8 times more likely to exceed customer acquisition goals than non-CSO led analytics.

“To achieve higher strategic influence of analytics, CSOs must lead when it comes to aligning analytics strategies to sales objectives and communicating insights from analytics,” continued Fischbein.

To achieve this change in behavior, Gartner suggests CSOs:

  • Deploy a decision driven analytics approach to prioritize the analytics that can have the most influence on the decisions that have the greatest impact.
  • Build specialization in their analytics organization that aligns with their top priorities.
  • Analyze seller performance metrics comparatively to drive actionability.

Photo by Amy Hirschi on Unsplash

Marketing analytics are only influencing 53% of decisions
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Marketing analytics are responsible for influencing just over half (53%) of marketing decisions, according to a survey by Gartner.

In May and June 2022, Gartner surveyed 377 users of marketing analytics to explore the role of marketing analytics in decision making.

“CMOs often believe that achieving marketing data integration goals will lead to greater influence and increased value of marketing analytics,” said Joseph Enever, Sr. Director Analyst in the Gartner Marketing practice. “The reality is that better data won’t increase marketing analytics’ decision influence alone. CMOs must address the real challenges — cognitive biases and the need for a data-informed culture.”

The survey found that the quantity of marketing decisions that analytics influences does matter: Organizations that report marketing analytics influence fewer than 50% of decisions are more likely to agree that they are unable to prove the value of marketing. Once marketing analytics teams cross that 50% threshold, there are likely diminishing returns to striving to increase the quantity of decisions influenced.

“By 2023, Gartner expects 60% of CMOs will slash the size of their marketing analytics department in half because of failed promised improvements,” said Enever.

Top Barriers to Marketing Analytics’ Influence: Data Quality Challenges and Cognitive Biases

Consumers of marketing analytics continue to cite evergreen data management challenges as the top reason analytics are not used when making decisions. The challenges of “data are inconsistent across sources” and “data are difficult to access” rose to the top in this year’s survey.

Marketing organizations regularly respond to these challenges by integrating more data or acquiring different technology seen as a fix-all approach to marketing data management — yet they fail to realize tangible impacts on key outcomes. For example, marketers experience diminishing marginal returns on data integration when pursuing a 360-degree view of the customer.

Barriers to the use of marketing analytics in decision making are not always caused by data integration challenges unique to marketing — rather, much of this boils down to people and/or process problems.

For instance, key cognitive biases are at the root of marketing analytics’ influence plateau. One-third of respondents reported that decision makers cherry-pick data to try to tell a story that aligns with their preconceived decision or opinion.

In addition, roughly a quarter of respondents said that decision makers do not review the information provided by the marketing analytics team (26%), reject their recommendations (24%), or rely on gut instincts to ultimately make their choice (24%).

CMOs must address these challenges by:

  • Tracking the decisions that are made based on analytics to provide a current state of view and areas to improve. Identify examples of marketing analytics work that provided actionable recommendations to a marketing campaign or program. Marketing leaders should encourage their team to look for patterns in decision-making habits and to document the types of decisions they influence.
  • Combatting cherry-picking. Set KPIs and metrics before launching a new campaign or marketing strategy, not after the data has already started to come in.
  • Encouraging senior leaders to set an example. Avoid being a HiPPO (Highest Paid Person’s Opinion) and actually allow data to inform, or change, decisions.
  • Establish analytics upskilling programs that account for differing workflows and resource constraints across the marketing organization. Build personas that detail how different employees need to use data in their roles and prioritize training sessions that best enable participants to learn the skills they need to perform their job.

Marketing departments ‘rely on outdated data and analytics practices’
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The majority of marketing departments still rely on outdated practices when it comes to marketing data and analytics, according to a new report.

Of the almost two-thirds of marketers surveyed by Adverity who believe their company is analytically mature, some 77% have yet to achieve a single unified view of their marketing performance while 68% still depend on spreadsheets for reporting.

At the same time, although 61% of marketing departments see developing predictive analytics as a key strategic aim in 2022, more than a third of those still struggle with manual data integration and some 48% say they do not trust the accuracy of their marketing data.

Conducted by Sirkin Research, the report surveyed almost 1,000 marketers and data analysts from around the world about their current data capabilities and aspirations for 2022.  Alongside businesses’ aspirations for predictive analytics, the research also revealed a worrying disconnect between analysts and marketers when it comes to understanding what their business’s current capabilities are.

For example, 60% of marketing data analysts say their organization already has the capacity to run predictive models, and yet only 42% of marketers agree. Similarly, although the majority (59%) of analysts say their company has a centralized data warehouse, only 43% of marketers say that’s the case.

“While the confidence of marketing departments in their analytical capabilities is commendable, that so many businesses are actually still struggling with the basics tells a very different story,” said Adverity CMO, Harriet Durnford-Smith.

Jeff Sirkin, CEO of Sirkin Research, added: “Yet, it’s the marketers who are actually the ones who should be utilizing those capabilities to make decisions and determine where budget is spent. If they don’t know what their company’s current capabilities are, this not only hinders their effectiveness, it is also a waste of money for the business. As such, bridging this divide should be a top priority for CMOs in 2022.”

The new research comes on the heels of Adverity’s “Marketing Analytics State of Play 2022: Challenges and Priorities” research report, which outlined the pain points facing modern marketers and data analysts–most notably, a lack of trust in the data. This new report builds out further how marketers can reflect on the challenges that they currently face and helps to identify solutions that will provide guidance for how to prioritize modernization in 2022.

Google Analytics Segments Vs Filters
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By Ben Johnston – Head of SEO & Data Analytics – ESV Digital

Learn the difference between Google Analytics segments and filters, what they are, how they work and when you would use each of them...

One of the most common questions I’m asked about Google Analytics is the difference between a segment and a filter and the main use case of each of them. I’m often asked why you would ever use a filter when a segment does the same job and vice versa.

In today’s post, I’m going to briefly run you through what segments and filters are, how they work and the reasons for using each of them.

WHAT IS A GOOGLE ANALYTICS SEGMENT?

A segment in Google Analytics lets you view your metrics based upon specific criteria, for example only organic or paid traffic. They allow you to change your data on the fly and you use the whole of the Google Analytics interface just focusing on that data and, crucially, they do not change your data the way a filter does.

A segment can be applied retroactively, so you can see how your organic performance was last year and so on, and you can also create your own segments based on certain specific conditions. You can even share those custom segments with other Google Analytics users.

You can apply a segment to your Google Analytics like so:

Click the Add Segment button and you’ll see the list of pre-configured ones. As you can see, there’s a lot to play with and with the ability to import new segments from the Google Analytics gallery and create your own, there’s plenty of flexibility there to investigate your data from a variety of perspectives.

Segments are great and an essential part of your Google Analytics arsenal, but they’re not without their weaknesses.

Weaknesses Of Segments

As handy as it is being able to alter your data on the fly, there is inherently some lost functionality compared to filters. Firstly, there is less flexibility in what you can do with a segment than a filter – you cannot exclude a specific IP address or series of IP addresses with a segment, for example.

They also have a habit of triggering sampling within Google Analytics, where the data shown in a report is less than 100% accurate. If your dataset is small, you should be OK, but segments do bring this on much sooner.

WHAT IS A GOOGLE ANALYTICS FILTER?

A filter is applied to a Google Analytics view and permanently changes the way that the data is collected for that view, rather than changing the way it’s reported on the fly. Unlike a segment, a filter will not change your data retroactively.

Filters offer a great deal more functionality than segments – as well as just replicating the capacities of segments, which would be prudent if you have a high amount of traffic, you can also make sweeping changes to the way your data is collected, processed and reported. You can use a filter to rewrite the URLs in your page reports, for example, or to double-check the hostname or simply to exclude a section of traffic which you know is not relevant (your own team, for example, or bots). You can also unleash the power of regular expressions to really take control of your data.

Filters are a far more powerful solution than segments, but they don’t offer the same flexibility. You would use a filter for a specific task within a reporting view (excluding your own office’s traffic, for example), rather than using it to check the performance of a specific metric in most cases.

Weaknesses Of Filters

With the power of filters comes responsibility in their use. They permanently change the data in a view from the moment they’re applied to the moment you remove it. There’s no going back. They also can’t be applied retroactively in the same way a segment can. It’s this permanence, plus the additional Google Analytics knowledge required to set up a filter that is the key weakness of them.

In line with best practice, you should always have a completely unfiltered “All Website Data” view, to ensure data continuity and to use for checking that your data is coming through properly. You should then have other filtered views depending on the kind of requirements your site has.

At the very least, we suggest having the All Website Data view and a view which filters out your own IP address and the IP address of any partner agencies/ other offices etc, although we would typically go much deeper than this with a Google Analytics setup.

WHEN TO USE SEGMENTS & FILTERS

A segment is the best way to isolate a certain metric, channel or device in your reporting view and apply that to your historic data. If you want to see how many people have come to your site over the last three years from Facebook on their tablets, a segment is the way to go.

If you need to permanently change the way your data is collected, such as excluding your IP address, removing bots, or rewriting your URLs so that they’re easier to read in reports, you’ll be looking for a filter.

The key thing to understand about filters vs segments is that there is really no “vs” at all. They’re different tools for different tasks and a good setup uses them together. For most reports, you’ll be relying on segments to isolate and highlight different metrics, but to ensure that your data is as clean as it can be, you’re going to need filters to be involved.

Unsure of how well your Google Analytics setup stands up to best practice? Get in touch with ESV Digital and let us see what we can do to help. Follow us on Facebook and Twitter for the latest updates.

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