The In-Sourced Analytics Revolution: Leveraging Popular Tech for Sales & Marketing Transformation

AI and Machine Learning have been reshaping industries for the last 5-10 years, and businesses, regardless of size, find themselves at a crossroads. Leveraging popular tech stacks and tools has become critical for staying competitive. Tech giants like Microsoft and Google have accelerated their cloud infrastructure and analytics offerings, enabling more innovative, more informed decision-making in Sales and Marketing.

Popular technology is evolving fast, and its capabilities will accelerate as Microsoft and Google dominate the end-to-end analytics space. 

Microsoft Azure:

Launched with basic cloud services, Azure offers advanced AI and ML capabilities, enabling real-time analytics and large-scale machine learning operations with standard APIs for all sorts of business problems that ML can solve.

Power BI:

It has evolved from a simple data visualization tool 8-9 years ago to a comprehensive analytics platform with integration capabilities for R and Python. Now supports advanced analytics, enabling users to create diagnostic and predictive platforms, challenging thousands of domain software products.

Microsoft Power Automate:

Transitioned from a basic automation tool to an integral part of Microsoft's business process automation with AI-driven capabilities. Enables seamless workflow automation across various applications, reducing manual workloads and increasing operational efficiency. We at Revology Analytics have been leveraging Power Automate to streamline dozens of workflows that would otherwise take two full-time employees to do.

Azure Data Factory:

Started as a data integration service, it now facilitates complex data pipelines and ETL processes for large-scale data engineering projects. It integrates well with Sharepoint, Azure Machine Learning, and Power BI, providing end-to-end data processing and analytics solutions. It has turned into a strong rival for products like Alteryx.

Tableau:

Initially focused on data visualization a little over a decade ago, Tableau has expanded to include interactive, AI-driven insights and predictive analytics. Like Power BI, it integrates with Python and R for advanced statistical analyses alongside natural language processing (NLP) for more intuitive data exploration.

Google Cloud:

Google Cloud's advancements include state-of-the-art AI and ML services like AutoML and domain-specific APIs, offering customized model training without extensive coding knowledge.

Enhanced data warehousing capabilities with BigQuery, allowing for faster, more efficient processing of massive datasets, including GA4 data for digital marketing analytics.

Companies that have capitalized on these capabilities have increased their customer engagement and share of wallet and raised overall profitability.

Sample list of popular tech stack


The Most Impactful Approach to Revenue Growth Analytics: In-Sourcing

Despite these advancements, companies still face a significant challenge with the overwhelming presence of "turnkey" software products. With well over 10,000 Sales and Marketing Enablement SaaS products in the marketplace, discerning which truly delivers value is challenging. Many of these solutions, while promising, fall short of fulfilling their potential, leaving businesses in a predicament after spending 6-7 figures on solutions each year.

Our research shows that firms who use home-built solutions for Sales Force and Marketing Effectiveness have greater levels of Revenue Analytics Maturity than those who rely on software vendors or information providers. This intuitively makes sense but underscores the importance of "owning" your data and analytics journey.

10,000 SaaS solutions for Marketing and growing

The answer to the above challenge is a more strategic approach - one that raises the overall analytics maturity of a company and frees companies from vendor and agency over-reliance. This approach builds Sales and Marketing Analytics capabilities in a highly collaborative manner with decision-makers and end-users, achieves far greater tool adoption, and ultimately drives profitable growth.

Popular tech stacks and tools, like Microsoft's Power Platform and Azure or Google Cloud Platform AI and ML solutions - can empower companies to develop bespoke, best-in-class capabilities in critical areas of Sales and Customer Growth Analytics.

These tools are familiar to most businesses and IT teams (think Power BI, Azure, Power Automate, etc.), thus requiring minimal incremental investment and providing a robust foundation for building sophisticated analytics solutions. By crafting and owning these commercial analytics capabilities, companies stand a much higher chance of becoming genuinely insights-driven and reducing dependence on external vendors or 3rd party solutions.


Key Industry Pain Points in Sales & Marketing Analytics

  1. Data Overload, Limited Insights: Sales and Marketing leaders are overwhelmed by data but lack advanced tools for meaningful analytics. The market is flooded with over 8,000 expensive and uncoordinated "turnkey" solutions, providing limited predictive/prescriptive insights.

  2. Challenges in Customer Dynamics: Companies struggle with mitigating customer churn and maximizing upsell/cross-sell opportunities. Over-reliance on ad agencies and difficulties in enhancing Customer Lifetime Value and optimizing the Marketing Mix are prevalent.

  3. Industry-Specific Analytical Gaps: Significant percentages of firms in CPG, Retail, Manufacturing, and Med-Tech sectors struggle to quantify the impact of marketing spend. Overall, 70% of traditional industry firms cannot measure the sales & profit impact of their marketing efforts.

  4. Inadequate Customer-Focused Tools: Two-thirds of companies lack effective customer-facing analytics tools for addressing customer pain points.

  5. Resource Intensive Manual Processes: Excessive time is spent on manual analytics and reporting, impeding the efficiency and speed of in-house analytics.


Some of the critical benefits of in-sourcing your Revenue Growth Analytics Approach

  • Utilizes Your Existing Tech Stack: Tailored solutions leverage existing infrastructure, avoiding the need for new, costly software implementations.

  • No Ongoing Vendor Reliance: Reduces dependency on external vendors for support.

  • Greater Control and Customization: Analytics models and tools are aligned with company-specific strategies and goals, offering real-time, actionable insights.

  • Co-Developed with Stakeholders and Decision-Makers: Ensures streamlined integration with existing business processes.


With the help of popular tech stack your company already has access to (or with minor upgrades/enhancements), your teams can build best-in-class capabilities for Sales & Customer Growth Analytics in the following areas:

Enhanced Sales and Marketing Analytics

  1. Sales Effectiveness Enablement: Our solutions focus on enhancing sales force effectiveness, providing tools for better productivity, customer relationship management, targeted engagement, and improved forecasting accuracy. This includes Sales & Customer Growth Analytics solutions like dashboards, forecasting tools, and AI-driven Sales Knowledge Graphs.

  2. Advanced Customer Segmentation and Behavioral Models: We employ machine learning models for audience optimization and segmentation, leading to higher revenue per customer, targeted sales strategies, and improved retention.

  3. Customer-Facing Analytics Solutions: Integrating analytics in customer-facing apps/websites aids in productivity, assortment/price/profit optimization, or market insights, driving customer differentiation and loyalty.

  4. Customer Data Enrichment: By enriching customer analytics with web tracking and third-party data, businesses can make more informed decisions, personalize marketing, and enhance sales efforts.

Marketing Growth Enablement

  1. Attribution & Machine Learning Models: Customized Marketing Mix Modeling and Multi-Touch Attribution facilitate optimized marketing spend, enhanced ROI, and data-driven growth strategies.

  2. Complete Customer Journey Analysis & Optimization: AI-driven Marketing Knowledge Graphs offer a holistic view of customer interactions, aiding in the development of more effective marketing strategies.

  3. Digital Channel Engagement Analysis: Utilizing dynamic digital analytics reporting tools like GA4, Power BI, Tableau, or Looker Studio provides accurate insights into digital engagement.

  4. Advanced Digital Marketing Insights: Dynamic dashboards and frameworks for performance analysis using existing cloud infrastructure and visualization tools provide clear marketing insights.


Becoming an insights-driven organization through organic capabilities is very much attainable nowadays. And it's much more than just about Sales & Marketing Enablement or other parts of Revenue Growth Analytics. By leveraging the full capabilities of only one tech stack, e.g., those of Microsoft, you can also build substantial data and workflow automation capabilities that save thousands of hours each year. 

As you navigate your Revenue Growth Analytics challenges, it's crucial to partner with experts who can guide this transformation effectively. Revelogy Analytics stands at the forefront of this revolution, offering tailored Commercial Analytics solutions that leverage AI/ML and your existing tech stack to unlock the true potential of your sales and customer data.

We invite you to explore how we can help accelerate your Sales and Marketing Growth through in-sourced Revenue Growth Analytics capabilities. 

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