🔥 What's New ?

👉 Amplitude acquires Kraftful: The union of quantity and quality

Amplitude announced on July 10, 2025 the acquisition of Kraftful, a startup specializing in AI-powered Voice of Customer (VoC). This acquisition marks a major strategic step in the product analytics industry, uniting quantitative behavioral data and qualitative user feedback in a native way for the first time.

Kraftful has developed a proprietary AI technology capable of transforming user feedback (support tickets, app store reviews, customer calls, online discussions) into clear actionable insights. Their specialized LLM can instantly identify priority feature requests, reveal user frustrations in their own words, and uncover invisible problems.

Integration into Amplitude will enable product teams to see not only what users are doing (via behavioral analytics), but also why they are doing it and how they feel. The platform will combine Session Replay, behavioral data, qualitative feedback, experimentation and surveys in a unified workflow.

ℹ️ For more information : Amplitude Acquires Kraftful to Power Customer-First Product ...
👉 At Starfox Analytics, we've developed a deep and diverse expertise in web analytics that enables us to effectively support our customers in the implementation and optimization of various sophisticated web analytics tools, such asAmplitude. Our personalized approach ensures that each solution is perfectly tailored to our customers' specific needs and strategic objectives, providing them with a comprehensive and actionable view of their digital data.

👉 Looker Studio: Code Interpreter preview

Google marked July 2025 with significant innovations across its analytics ecosystem.

Most notable is the introduction of the Code Interpreter in Looker Studio on July 25, radically transforming the platform's advanced analysis capabilities. This revolutionary feature translates natural language questions into executable Python code, enabling sophisticated analyses previously reserved for data scientists and data analysts. Code Interpreter supports statistical calculations, predictive modeling, time-series forecasting, and the generation of customized visualizations via the Python ecosystem.

The technical prerequisites are:

  • Looker Studio Pro subscription.
  • Gemini in Looker activated.
  • A Trusted Tester configuration in Google Cloud.
  • The feature operates with a limit of 5,000 rows per query and supports the main Python libraries for data science.

To activate the feature on Looker Studio (Pro):

1. In the left-hand navigation panel of Conversational Analytics, click on the Advanced Analytics button to activate Code Interpreter.

2. Once the code interpreter is activated, you can use Conversational Analytics to start conversations and ask questions about your data. Code interpreter uses the engine that powers Gemini chat to translate your queries into Python code and execute that code.

Example of a conversational Analytics analysis in Looker Studio
ℹ️ Find out more : Conversational Analytics Code Interpreter | Looker Studio ...
👉 At Starfox Analytics, we are actively supporting our customers in this transition by testing these new functionalities and iterating on their specific use cases. Our team works to develop prompt models tailored to the business needs of each sector, enabling our customers to take full advantage of these innovations while keeping their business expertise at the center of the analytical approach.

👉 Piwik Pro goes pay : End of the free Core offer

Piwik Pro is ending its free Core offer from December 2025, with automatic migration to the paid Business offer, and the new rates will be effective from August 4, 2025.

  • The Business offer targets SMEs looking for a cost-effective analytics solution that respects confidentiality.
  • The Enterprise plan offers three levels adapted to different stages of growth, from advanced marketing needs to highly regulated sectors
ℹ️ Find out more: Introducing new pricing: More analytics value and privacy co...
👉 At Starfox Analytics, we can support you in this transition by evaluating alternatives or optimizing your Piwik Pro investment according to your needs.

👉 Google Analytics: Reddit Ads data integration, Lead generation reports, and other improvements

Google marked July 2025 with significant innovations across its analytics ecosystem:

  • Reddit Ads data import: Native integration for automatic tracking of Reddit advertising costs in GA4
  • Lead generation reports: New "Lead Acquisition" and "Lead Disqualification and Loss" reports with 8 dedicated audience models, such as :
  • ⇒ Create an audience of "Qualified Prospects"to target these potential customers and encourage them to complete their conversion
  • ⇒ Create an audience of "Converted Prospects"to exclude current customers from your prospecting and remarketing campaigns
  • ⇒ Create an audience of "New Prospects"to be used in advertising campaigns to guide prospects towards conversion
  • Enhanced import of item (product) data: Support for item-scoped custom dimensions without the need for item IDs, this enhancement is particularly beneficial for companies with a large product catalog, as it allows simple integration of existing product data, without the technical complexity of mapping the data.
  • Analyst+ annotations: Users with the Analyst role or above can now create, modify and delete annotations.
ℹ️ What's new in Google Analytics - Analytics Help

👉 PostHog: New group and revenue analytics capabilities

PostHog enhanced its platform with several important features in July 2025. Group analytics now make it possible to analyze behavior at the level of organizations, teams or accounts, rather than just at the individual user level. This capability is crucial for B2B products where purchasing decisions involve multiple stakeholders.

Revenue analytics in beta offer precise tracking of financial metrics with hourly updated exchange rates and daily granularity. The platform also offers improved management of early access features, enabling users to easily subscribe and unsubscribe from betas.

ℹ️ Find out more: Documentation - PostHog

👉 Generative AI transforms dashboard creation

In its latest press release, Gartner predicts that 75% of content analytics will use generative AI by 2027 (including agentic AI), marking a fundamental transformation of the industry.

This development is accompanied by current mass adoption: 78% of organizations are already using AI in some form, and 68% of small businesses have adopted AI solutions.

Leading tools (Tableau Concierge, Power BI Copilot, Looker Studio Code Interpreter) can now create complex dashboards in minutes via natural language prompts. Gartner anticipates that 15% of daily work decisions will be made autonomously by agentic AI by 2028, compared with 0% in 2024.

The emerging challenge is that organizations need to develop new "prompt engineering" skills for analytics and establish validation frameworks for AI-generated insights. 80% of retail executives plan to adopt AI automation by the end of 2025.

ℹ️ Gartner Predicts 75% of Analytics Content to Use GenAI for E...

💡Tip of the month

Our "Tip of the month" section shares practical tips used daily at Starfox Analytics. These tips cover various Web Analytics tools to optimize your work. Don't hesitate to try them out and share them with your colleagues.

👉 BigQuery: GROUP BY ALL

Tired of manually listing all the non-aggregated columns in your GROUP BY clause? BigQuery has the solution!

The solution: GROUP BY ALL

Instead of writing :

SELECT
region,
category,
product_type,
COUNT(*) as total_sales,
AVG(amount) as avg_amount
FROM sales_data
GROUP BY region, category, product_type

You can now simply write :

SELECT
region,
category,
product_type,
COUNT(*) as total_sales,
AVG(amount) as avg_amount
FROM sales_data
GROUP BY ALL

How it works: BigQuery automatically detects all non-aggregated columns in your SELECT and uses them for grouping.

📖 Sharing Is Caring

Every month, our "Sharing is Caring" column presents an in-depth article on a current topic in Web Analytics. Our experts use their know-how and online resources to explore these topics in detail.

👉 Case study: Back Market migrates to server-side for +14% tracked conversions

This month, discover our business case on the server-side migration of our customer Back Market :

ℹ️ Back Market migrates to server-side for +14% tracked conversions

❤️ Best resources and articles of the moment

😜 Miscellaneous

👉 The rise of analytics professions: Data Analyst in the LinkedIn top 10

LinkedIn reveals in its Q2 2025 report that Data Analyst enters the top 10 most in-demand jobs (#10, +4 positions vs Q1), confirming the democratization of analytics in the enterprise. At the same time, Data Science Specialist is one of the fastest-growing jobs, with demand doubling (2.0x) compared to the previous quarter.

This development reflects the acceleration of digital transformation fueled by the adoption of AI. Companies are actively seeking profiles capable of bridging the gap between data and business decisions, creating new hybrid roles combining technical skills (SQL, Python, dbt) and business understanding.

Data Analyst salary 45-65k€ in France, Data Science Specialist 65-85k€, with significant bonuses for profiles mastering product analytics (funnels, cohorts, experimentation).

ℹ️ What Are the Most In-Demand Jobs?

🤩 Inside Starfox

👉 Reinventing e-commerce analytics: when data becomes strategy

"Simplicity is the ultimate sophistication." This quote from Leonardo da Vinci guides our approach at Starfox Analytics.

This month, the team took a major step forward by collaborating with an expert analyst designer on Looker Studio to revolutionize our dashboard deliverables.

Why this approach? Because we firmly believe that data exists only to serve decision-making. A dashboard is not a catalog of metrics, it's a tool for transmitting information that must guide action in a matter of seconds. Our obsession: transforming complexity into clarity.

BigQuery at the heart of everything. We systematically use BigQuery as our sole source of data. Not out of technological conformity, but out of strategic necessity. Machine learning calculations, advanced predictive audiences, behavioral segmentation models - all these require computing power that traditional tools can't offer.

The truth? 80% of our e-commerce dashboard indicators simply don't exist in GA4 or Piano Analytics. They exist nowhere else but in our vision of digital commerce.

Rethinking the customer journey. We've abandoned traditional metrics to build something radically different. Forget the conversion rate - that metric from the last century. We measure revenue per user, a true indicator of traffic quality.

Our revolutionary framework divides the customer journey into four fundamental stages of the customer mindset:

1. ENGAGEMENT - Awakening interest

The gap between the expectations of a visitor who has just clicked on a search result or advertisement and arrives on your site, and what you present to them, determines their motivation to continue their purchasing journey. Motivation is the most important factor in conversion.

We create a sophisticated engagement score by weighting each interaction according to its real importance. Every click, every scroll, every micro-moment counts in an algorithm that truly understands user intent.

2. SEARCH & FIND - Intelligent discovery

We measure search success from every angle: the rate of selection of a search result from among those presented, the % of sessions that result in a visit to a product page, or the % of search results that have no results or too few. It doesn't matter whether the discovery comes from navigation, the search bar or filters - we capture the real experience, adapted to each device, right down to the viewport level.

3. WANT & SELECT - Crystallizing desire

Percentage of users who progress from discovery to purchase intent. Adds to cart, meaningful engagement with product content based on number of visits to product pages, not just sessions.

4. TRANSACT - The final act

Here, we're no longer measuring the relevance of the offer, but the sheer efficiency of your transaction process. The ratio between actual purchase and start of checkout reveals hidden frictions when the prospect has already made his decision a priori.

The power of perspective. Each KPI lives in an ecosystem of comparisons: previous period, temporal evolution, perspective with other indicators. The add-to-cart rate, for example, takes on its full meaning when compared with the number of product pages viewed.

Multidimensional analysis. Once these foundations have been laid, analysis explodes its limits: user segments, campaigns, channels, visitor types, products, categories, checkout methods. Each angle reveals an actionable truth.

Less, but better. We propose relatively few indicators. But each one is relevant, actionable and comparable. Each tells a part of the story that leads immediately to the next action.

A need, a question?

Write to us at hello@starfox-analytics.com.
Our team will get back to you as soon as possible.

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