How to Choose Analytics Tools for B2B Ads

Henry McIntosh
2 days ago
14 min read

Choosing the right analytics tool for B2B advertising can directly impact your revenue by ensuring you track and optimise the efforts that matter most. Here’s a quick summary of what to focus on:

Set Clear Goals and Budget: Define your advertising objectives (e.g., lead generation, ABM) and calculate total costs, including setup, licensing, and integration.
Prioritise Features: Look for multi-touch attribution, customisable dashboards, and CRM integration to track the entire customer journey and link ad spend to revenue.
Ensure Compliance: Choose tools that meet GDPR and other data security standards, especially if operating in regulated industries.
Check Integration: Ensure the platform integrates smoothly with your existing CRM, marketing tools, and ad platforms to avoid data silos.
Test Before Committing: Use trials or sandbox environments to confirm usability, data accuracy, and workflow compatibility.

Key Takeaway: The best analytics tool aligns with your goals, integrates with your tech stack, and provides actionable insights to optimise your ad spend.

11 Best Digital Analytics Tools in 2025 (Ranked by Categores & Use Cases)

Set Your Advertising Goals and Budget

Before diving into analytics platforms, it’s crucial to establish clear goals and a realistic budget. This step ensures you don’t end up with tools that either include unnecessary features or lack the essentials for your specific needs.

Match Analytics Tools to Campaign Objectives

Your analytics requirements will depend heavily on the type of campaign you're running - whether it’s lead generation, account-based marketing (ABM), or prospect nurturing. Each approach comes with unique tracking demands. For example:

Lead generation relies on tools capable of tracking conversions and monitoring form submissions.
ABM requires platforms that can identify and track engagement at an account level, rather than just individual visitors. In fact, ABM strategies have proven highly effective, with 70% of B2B marketers reporting increased revenue after adopting ABM in 2023. Additionally, ABM strategies deliver a 97% higher ROI compared to other B2B marketing tactics [12].

To ensure your analytics platform aligns with your goals, consider using the SMART framework. For instance, you might aim to increase marketing-qualified leads (MQLs) by 30% in Q4. This approach helps you focus on the key metrics relevant to each funnel stage - whether it’s impressions for building awareness, engagement metrics during content interaction, or conversion rates for measuring revenue impact [8][9].

Customise dashboards based on the needs of your stakeholders. For example:

CEOs often prioritise metrics like overall ROI and revenue growth.
Marketing Managers need detailed insights into campaign-level performance.

Keep dashboards streamlined - limit them to five to seven core KPIs to avoid overwhelming users with data. For example, Paylocity saw a 62% increase in conversion value by strengthening its data and measurement foundations [10]. A focused dashboard ensures you’re tracking what matters most [8].

Assess Budget Constraints and Cost-Effectiveness

Evaluating your budget isn’t just about the upfront costs. You’ll need to calculate the Total Cost of Ownership (TCO), which includes setup, licensing, hosting, and ongoing support.

For example, while Google Analytics is free, its data sampling limitations can hinder large campaigns. Google Analytics 360 eliminates these constraints but comes with a higher price tag, which might not suit smaller B2B teams [8].

Advertising costs are also climbing. In the first quarter of 2022, cost-per-click for search ads rose by 12% year-on-year, with some B2B keywords exceeding £75 per click [11]. As Katie Rigby from Ruler Analytics puts it:

With the rising cost of PPC, the ability to track ad success is more important than ever, to make sure every pound matters [11].

Don’t forget to account for integration and ETL (Extract, Transform, Load) costs if you’re consolidating data from multiple sources. Tools like Fivetran or Stitch can automate these processes, but they add to monthly expenses [8]. Additionally, check whether technical support and implementation services are included in the package or require separate agreements.

For organisations in regulated industries, on-premise or private-cloud hosting options may be necessary to ensure data sovereignty. However, these options tend to be more expensive than standard cloud-based solutions [7][8]. Whatever your setup, aim for a Return on Ad Spend (ROAS) of at least 3:1 to justify your investment [8].

Identify Required Features for B2B Analytics

Once you've aligned your budget, the next step is identifying the must-have features for your analytics platform. For businesses in regulated industries, the requirements often go far beyond basic metrics like click tracking.

Multi-Touch Attribution and Conversion Tracking

In B2B, purchase decisions typically involve multiple stakeholders, making it essential to attribute value to every touchpoint in the customer journey.

Your platform should be capable of assigning fractional credit across these touchpoints. Why? Because data-driven attribution can increase efficiency by 15–30% [13]. The tool must track every interaction along the customer journey, ensuring nothing is missed.

Customisable lookback windows are equally important since B2B sales cycles often span 30 to 90 days [13]. For example, Google Analytics 4 uses a default 30-day window for acquisition events and 90 days for other conversions [13]. Yet, 41% of B2B marketers still struggle to gain a clear view of the customer journey [13].

Additionally, your tool should track both online and offline conversions through CRM integration. Platforms like Ruler Analytics (starting at £199/month) can dynamically insert numbers to track which ads lead to phone enquiries. Advanced CRM integrations with tools like Salesforce or HubSpot can even connect online ad clicks to closed-won deals, offering true revenue attribution rather than just counting leads [13][14].

Once you've nailed down attribution, the next priority is ensuring your insights are presented in a way that's actionable and easy to understand.

Customisable Dashboards and Reporting

Generic dashboards simply won't cut it for B2B analytics. You need account-level visibility that consolidates data by company rather than individual users - especially crucial for account-based marketing campaigns where multiple decision-makers from the same organisation interact with your ads.

Your dashboards should highlight key B2B metrics, such as MQL-to-SQL and SQL-to-Opportunity ratios, to quickly identify where your funnel might be leaking [3][15].

Role-specific views are another must-have. They ensure stakeholders only access data relevant to their responsibilities, while also maintaining data security [3].

For businesses in regulated industries, dashboards must comply with data residency requirements. For instance, the Colruyt Group used Tealium iQ to manage customer data while adhering to GDPR. This approach not only ensured compliance but also provided deeper insights into first-party data, delivering a rapid return on investment [16].

Keep in mind that B2B data decays at an average rate of 30% annually, so real-time updates in your dashboards are critical for maintaining accuracy [3].

Once your dashboards are set, the next step is ensuring your platform meets strict data security and compliance standards.

Data Security and Compliance Features

For B2B advertisers targeting audiences in the EU or UK, compliance with GDPR, the ePrivacy Directive, and the DMA isn't optional - it's a legal requirement [17].

Start by ensuring your platform integrates with Consent Management Platforms (CMPs) and supports Google Consent Mode v2. This version, mandatory from March 2024, introduces two new consent fields: "Ad User Data" and "Ad Personalisation" [17].

IP anonymisation is another essential feature. The tool should automatically remove the last octet of IPv4 addresses (or the last 10 octets for IPv6), a critical requirement in sectors like financial services and pharmaceuticals where trust hinges on rigorous data governance [17][18].

Data residency is also key. Platforms like HubSpot and Salesforce Account Engagement offer EU and UK data centre hosting, ensuring your analytics data remains within regional jurisdictions [18]. This is particularly important given that the global average cost of a data breach now stands at approximately £3.6 million [3].

As OneTrust aptly puts it:

"Privacy has become a cornerstone in the digital advertising world. By striking a healthy balance between data privacy and personalisation, advertisers can maintain user trust while improving the durability of their ad measurement." [17]

Finally, check who owns your data. Some free or low-cost tools may retain partial ownership, especially if they process data through US-based servers. For regulated industries, full data ownership and transparent processing agreements are non-negotiable [18].

Check Integration Capabilities with Existing Platforms

Once you've ensured your analytics tool meets all security and compliance requirements, the next step is to evaluate how well it integrates with your existing technology stack. Poor integration can lead to isolated data silos, forcing you into time-consuming manual reporting processes that are prone to errors [19].

For B2B advertisers, smooth integration isn't just nice to have - it’s essential. It can mean the difference between guessing which campaigns drive revenue and having a clear picture of where every pound of ad spend is going. Pay particular attention to how native connectors simplify integration with CRMs and marketing platforms.

Integration with CRMs and Marketing Platforms

To truly link marketing efforts with revenue outcomes, your analytics tool needs to connect directly to your CRM. Bidirectional synchronisation is key - it allows the tool to send lead data to the CRM while also pulling back revenue and deal-stage information into your analytics platform [18].

This two-way connection is what makes accurate ROI calculations possible. Tools like Ruler Analytics excel at this by pulling revenue data from CRMs such as Salesforce and HubSpot, enabling closed-loop revenue tracking [18]. Without this synchronisation, your metrics will lack depth and fail to provide actionable insights [18].

Native connectors are a game-changer, as they simplify setup compared to API-based integrations. For example, HubSpot offers a native, bidirectional sync with Salesforce, while Salesforce Account Engagement (formerly Pardot) provides real-time synchronisation of leads and opportunities - ideal for companies already using Salesforce [18]. These integrations pave the way for automated workflows, reducing the need for manual data exports.

Before committing to any analytics tool, take stock of your current platforms - like Google Ads, LinkedIn Campaign Manager, Meta Ads Manager, and any marketing automation software - and ensure the tool offers native connectors for each. Adverity, for instance, connects to over 600 data sources through its extensive connector library, eliminating the need for custom engineering work [19].

Platform	CRM Integration Type	Monthly Starting Price	Key Benefit
HubSpot	Native / Bidirectional	£16 (Starter)	All-in-one platform; user-friendly
Salesforce Account Engagement	Native (Salesforce)	£1,000	Real-time sync of leads and opportunities
Ruler Analytics	Wide Integration	£199	Pulls revenue data back from CRM to ads
Microsoft Power BI	Connectors / APIs	£7.50/user	Advanced visualisation; integrates with Office 365

Automation and Workflow Optimisation

Seamless CRM connections lay the groundwork for automation, which eliminates the need for manual data handling. Manual exports not only waste valuable time but also divert focus from campaign optimisation [19].

For example, if a lead from a LinkedIn campaign revisits your pricing page, the system should immediately alert your sales team via the CRM [18].

Real-time synchronisation is especially critical for B2B sales cycles. Delayed data updates - whether hourly or daily - can result in missed opportunities to optimise campaigns. If your analytics platform only provides yesterday’s performance while your competitors are making real-time adjustments, you’re already at a disadvantage [19][9].

Compare and Select the Right Analytics Tool

B2B Analytics Tools Comparison: HubSpot vs Google Analytics vs Salesforce vs Marketo vs Looker vs AgencyAnalytics

When it comes to choosing the right analytics tool, focus on three key aspects: attribution, integration, and scalability. Many B2B advertisers find themselves overwhelmed by endless feature lists and pricing options. The best approach? Narrow it down to what truly matters - select a tool that translates your advertising goals into actionable insights.

A clear, structured comparison can help you cut through the noise. The right tool should give you visibility into the entire customer journey - not just surface-level metrics like website traffic or lead form submissions. Below, we’ve outlined how some of the top platforms stack up for different B2B needs.

Comparison of HubSpot, Google Analytics, and Salesforce

Each of these platforms has a distinct focus for B2B analytics. HubSpot is built for inbound marketing and lead scoring, making it a great option if your strategy revolves around content and nurturing leads [20][1]. Google Analytics (GA4) shines in analysing website behaviour and conversion paths, especially when used alongside Google Ads [6]. Meanwhile, Salesforce is designed to directly connect marketing spend to revenue, making it ideal for organisations prioritising sales alignment [1].

Feature	HubSpot	Google Analytics (GA4)	Salesforce
Primary Strength	Inbound marketing, lead scoring, automated reporting [20][1]	Website traffic, user behaviour, conversion tracking [1]	Links marketing to sales revenue and pipeline [1]
Integration	Native CRM and email marketing [20]	Deep integration with Google Ads and BigQuery [6]	Strongest integration with sales data and revenue metrics [1]
B2B Focus	High; focuses on MQL/SQL segmentation [20]	General; requires custom setup for complex funnels [2]	High; designed for complex sales cycles [1]
Multi-Touch Attribution	Available in Professional/Enterprise tiers	Custom setup required	Native revenue attribution

Your decision will often depend on your current setup. For example, if your team already uses Salesforce as its CRM, adding Account Engagement (formerly Pardot) ensures a seamless flow from ad click to closed deal. If your focus is on granular website data and you heavily rely on Google Ads, GA4 is a natural fit. On the other hand, HubSpot is perfect for companies building an all-in-one marketing and sales platform from the ground up.

Comparison of Marketo, Looker, and AgencyAnalytics

For more complex requirements - especially in regulated industries - consider tools like Marketo, Looker, and AgencyAnalytics. Marketo (part of Adobe) is known for account-based attribution and lead journey orchestration, making it a strong choice for enterprise teams running sophisticated campaigns [23]. Looker, a business intelligence platform, excels in connecting to data warehouses like BigQuery and Snowflake, offering custom SQL-based analysis for data-heavy teams [2]. AgencyAnalytics, on the other hand, focuses on reporting automation, simplifying performance tracking across multiple platforms into easy-to-read dashboards [21][5].

Marketo’s standout feature is its "every-touch" attribution model, which maps the entire buyer journey across multiple stakeholders. Looker, while requiring more technical expertise, offers unparalleled flexibility for organisations with large datasets. AgencyAnalytics provides a simpler solution, automating cross-channel reporting without the need for SQL knowledge.

Factor	Marketo (Adobe)	Looker (Google Cloud)	AgencyAnalytics
Primary Use Case	Lead/account journey orchestration [23]	BI and data warehouse exploration [2]	Reporting automation and dashboards [21]
Attribution Strength	Advanced every-touch and account-based [22][23]	Custom modelling via SQL/data warehouse [2]	Cross-channel performance overview [5]
Integration Focus	CRM and marketing automation [23]	BigQuery, Snowflake, Redshift [2]	PPC platforms (Google, LinkedIn, Meta) [5]
Target Audience	Enterprise B2B marketing teams [23]	Data analysts and BI teams [2]	Marketing agencies and performance teams [21]
Scalability	High (complex B2B go-to-market) [23]	High (large data volumes) [2]	Moderate (reporting-focused)

Choosing the right tool depends on your team’s capabilities and goals. Marketo is best for organisations with dedicated marketing operations teams to handle its complexity. Looker is ideal for data analysts comfortable working with SQL queries. Meanwhile, AgencyAnalytics is easier to implement but may lack the depth needed for intricate attribution models. As Lever Digital aptly puts it:

The job now isn't to find a perfect model. It's to build a robust, honest view of PPC's role in driving revenue [5].

Test and Measure Tool Performance

Once you've evaluated the integration, the next step is to put the tool through its paces in real-world scenarios. Take advantage of free trials or sandbox environments offered by most platforms to simulate actual workflows. During this trial, focus on verifying key functionalities: seamless CRM integration, user-friendly dashboards, and reliable data consistency. For example, cross-check form submissions in the analytics tool with your CRM records to identify any mismatches [8]. Also, ensure tracking pixels are firing as expected. This hands-on testing phase is critical for uncovering both technical and usability aspects of the tool.

Pay close attention to usability and data quality. The tool should be intuitive enough for non-technical team members to generate reports without difficulty. Additionally, confirm that the data remains unsampled as your traffic scales. Establish a consistent review schedule - daily for urgent issues, weekly for tactical adjustments, and monthly for deeper insights [9]. This rhythm will help you determine if the tool aligns with your team's day-to-day workflow rather than just its theoretical capabilities.

When measuring performance, focus on KPIs that truly matter. Instead of relying solely on MQLs or impressions, track metrics like SQOs and revenue [11][15]. Aiming for a ROAS of at least 3:1 is a good benchmark. Keep dashboards streamlined by limiting them to five to seven core KPIs [8]. As Tommy Wiles, Global Senior Analytics Manager at Google, emphasises:

Testing and experimentation are essential to understanding how new privacy-safe tools can help [24].

Beyond the numbers, gather qualitative feedback from your team. Ask them how the tool impacts their workflow: Does it save time or add unnecessary steps? Can it push engagement data directly to your CRM, or does it require manual exports? Ensure the terms of service clearly state that your organisation retains ownership of exported analytics data - this is especially crucial when working with free tools [7]. A tool that looks ideal on paper but frustrates your team in practice won't justify the investment. Ultimately, it needs to deliver both actionable insights and operational efficiency to make a positive impact on your advertising ROI.

Conclusion

Selecting the best analytics tool for B2B advertising isn’t just about ticking off a list of features - it’s about ensuring the tool aligns with your business goals and integrates smoothly with your existing systems. Start by defining clear success metrics - whether it’s lead quality, revenue attribution, or pipeline velocity. This helps you focus on metrics that truly matter for driving business results, rather than getting lost in vanity metrics like clicks or impressions [25].

Once you’ve narrowed down your options, the testing phase is where theory meets practice. Use a proof-of-concept test with real company data to evaluate the tool’s performance. Make sure to involve key stakeholders from marketing, sales, and finance to ensure the tool meets cross-departmental needs. Pay particular attention to CRM data reconciliation during this phase to avoid creating reporting inconsistencies. As April Robb, an Event Marketer, puts it:

Analytics that stop at reporting activity fail... Analytics that connect activity to outcomes enable better decisions, tighter forecasts, and more productive conversations with finance and sales. [4]

After confirming the tool’s performance through testing, consider how it supports long-term ROI and budget efficiency. Strategic attribution, for instance, has the potential to improve marketing ROI by up to 20% [13]. However, this only works if you choose a platform that fits the complexity and length of your sales cycle while ensuring compliance, scalability, and account-level insights. As highlighted earlier, tools that combine reliable attribution with seamless integration are the ones that truly make a difference.

Whether you go for Google Analytics 4 or a specialised B2B analytics platform, the right choice will transform data into actionable insights. This not only optimises budget allocation but also clearly demonstrates the impact of your advertising efforts.

FAQs

How can I choose the right analytics tool for my B2B advertising goals?

Choosing the right analytics tool begins with a clear understanding of your B2B campaign goals. Are you aiming to generate more qualified leads, shorten the sales cycle, or prove ROI? Once your objectives are clear, connect them to measurable KPIs - think cost-per-lead, pipeline contribution, or customer acquisition cost. This way, you can focus on tools that deliver the data you need to track progress effectively.

Take stock of your current data sources, including your CRM, ad platforms like LinkedIn or Google Ads, website analytics, and even offline interactions. The ideal tool should integrate seamlessly with these systems, giving you a complete view of your buyer's journey. For B2B campaigns, tools with multi-touch attribution capabilities and the ability to link marketing spend directly to revenue can be game-changers.

Don't forget to factor in your budget, scalability, and organisational needs. Features like customisable dashboards for reporting, predictive analytics to prioritise leads, and flexible pricing models that grow with your business can make a big difference. Running a brief pilot programme is a smart way to test usability and ensure the tool fits your needs. For expert guidance, Twenty One Twelve Marketing can help you transform complicated data into actionable insights tailored to your market.

What should I look for in an analytics tool to ensure compliance with UK data protection laws?

When choosing an analytics tool for B2B advertising, it's essential to focus on features that align with UK GDPR and other data protection laws. Start by ensuring the tool supports Data Protection Impact Assessments (DPIAs) and keeps a comprehensive audit trail of data processing activities. This helps showcase accountability and mitigates risks to individuals' rights.

The platform should also offer granular access controls and robust encryption (both in transit and at rest). These measures protect sensitive data and ensure only authorised personnel can access it. Additionally, the tool should include features for managing data-subject rights, such as the ability to locate, edit, export, or delete personal data swiftly, making it easier to handle subject access requests.

Finally, prioritise tools with data localisation options that allow data to be stored within the UK or EU, if necessary. Features like privacy-by-design - for example, automatic anonymisation or consent management integrations - are also key. These not only help you meet legal requirements but also show a strong commitment to responsible data handling, enabling you to improve ad performance while staying compliant.

How can I integrate my analytics tool with existing CRM and marketing platforms seamlessly?

To seamlessly connect your analytics tool with your existing CRM or marketing platforms, start by taking stock of all the systems you currently rely on - whether it’s Salesforce, HubSpot, or others. Identify the key data fields you'll need, such as lead ID, company name, deal value (£), and campaign dates (dd/mm/yyyy). Opt for a tool that either comes with built-in connectors for these platforms or supports flexible APIs for custom setups.

Consistency is key, so make sure data formats are aligned across all systems. Standardise field names, date formats, and UK-specific conventions like currency (£) and numbers (e.g., 1,000.50). Before going all in, test the integration using a small data set to ensure everything is accurate, spot any errors, and confirm that metrics are syncing correctly between platforms. Automating data refresh schedules and maintaining clear, detailed documentation will keep your workflow smooth and dependable for the entire team.