Fact: Data guides SaaS business decisions.
But what if the data itself becomes a hurdle due to its limited scope?
We’re talking about the Business Intelligence (BI) solutions that are supposed to empower your go-to-market (GTM) teams with actionable insights. Still, many of you might experience that the BI tools fall short of expectations.
Result?
Frustrated and confused GTM teams.
Buying a highly-rated BI platform isn’t an antidote to concrete data-driven decision-making
Because GTM teams function in the areas of high stakes where missed opportunities, slow response times, and misaligned strategies can cost you dearly. Often, the culprit behind these issues can be your BI solution.
Let's explore the reasons behind these failures.
1. Poor Adoption of Existing Tools
Are your GTM teams well-equipped to extensively use BI tools for best results? How do you gauge whether they are adopting these tools right?
Otherwise, these investments won’t generate any value.
BI tools have 26% of global adoption rates, which means, it is a common pain point.
Also, its flexibility is the top issue amongst BI users.
But then, such low adoption is often a symptom of deeper issues that present bottlenecks to integrating these tools into their everyday workflows.
Let’s explore those.
- Pre-Made Dashboards
Out-of-the-box BI fails to address the specific needs of GTM teams and generic metrics may not align with your unique sales funnel. Chances are, GTM team executives may get overwhelmed with irrelevant data or, worse, missing critical insights.
- A Disconnect between Platform and Workflow
Let's assume you have the best possible and powerful BI solution. But, what if it fails to seamlessly integrate into your team's existing workflow?
That’s a red flag since it invites friction within the team.
It forces GTM teams to switch between multiple tools and platforms to get a clear picture.
For example, marketing teams looking to track real-time campaign performance will find static, inflexible reports frustrating.
2. Your Team Waits Too Long for the Analysis
BI solutions are prone to taking a long time to offer a meaningful, in-depth analysis. But, your GTM teams do not have enough time and patience to wait in a highly competitive SaaS space.
And this cripples your GTM team’s effectiveness.
Traditional BI tools are built for reporting on what's already happened, not for the in-depth analysis that drives strategic decision-making.
They fall short in several key areas as below -
- In-Depth, Complex Analysis
Traditional BI dashboards are ideal for surface-level metrics, simple reporting, and basic data visualization. But it crumbles when you need to single out a particular "why" behind the numbers. Most lack the capabilities to handle complex statistical models or advanced analytics techniques.
Impact: Missing critical trends and patterns that could inform strategic decisions.
For example, BI will tell you that the churn rate is increasing. But it won’t dwell on identifying the root causes — product features, pricing changes, or customer segments.
- Root-Cause Analysis
Successful SaaS businesses thrive on identifying factors that hinder their performance. For this, GTM teams require diving deeper into customer behavior, market trends, and competitor strategies. This is where BI tools hit the roadblock.
You only get a snapshot of insights. For in-depth uncovering, run complex queries and perform manual data wrangling.
Impact: Inability to deal with root cause analysis would mean implementing fixes that address symptoms rather than the actual problems. It results in recurring issues and wasted resources.
Ideally, you’d want to automatically identify the key factors driving a particular outcome so that your GTM teams pivot to strategic decision-making.
- Customer Segmentation and Churn Forecasting
When GTM teams can’t segment customers, they miss opportunities to personalize their experience and address their unique needs.
This leads to increased churn, especially when prospects transition from a free trial to a paid subscription.
Impact: Traditional BI tools can’t perform advanced segmentation like analyzing behavioral data. This means you’re overlooking customers at risk of churning.
While lack of segmentation is still manageable if you get the accurate churn forecasting — a lifeline. That way, you can at least allocate resources for retention efforts.
However, standard BI tools struggle with churn forecasting because:
- Historical data on churn doesn’t account for shifts in customer preferences or external factors that influence churn.
- Static models fail to adapt to changing customer dynamics, rendering predictions less accurate over time.
3. BI Can’t Help Outside of What You Ask for
BI solutions are exceptional at answering the questions you explicitly ask. But what happens when you don’t know what insights to look for?
This is a classic case of —
It can make GTM teams tunnel-visioned to specific metrics or KPIs. This means they won’t ever discover hidden patterns or emerging trends that could significantly impact their strategies.
As a result, they may miss out on critical data opportunities and critical insights they weren’t looking for.
Result?
Limited insights.
- Limited Insights from Pre-Defined Queries
Traditional BI tools are built around predefined queries and reports. These are useful yet very limited to what you’ve already identified as important.
Impact: Missed opportunities as below.
- Missed Revenue: Failing to identify potential growth areas or underserved customer segments.
- Inefficient Marketing: No holistic view of the customer journey may miscredit your marketing efforts, leading to wasted resources and suboptimal results.
- Competitive Disadvantage: Your GTM team could be left playing catch-up as your competitors may jump ahead by uncovering hidden insights and adapting their strategies.
4. Operationalizing Data Science Insights Tough with BI Tools
Businesses these days rely much on -
- Data science — Predicted to reach US$501.03 billion by 2032.
- Machine learning (ML) — Projected for US$79.29bn in 2024.
- Predictive analytics — expected to grow from $18.02 billion in 2024 to $95.30 billion by 2032 (at 23.1% CAGR).
The large (and growing) market shares are a testament to the immense potential.
Here, the traditional BI tools struggle to operationalize in these areas.
Your GTM teams can push their limits if there’s a tool designed to bridge the gap between data science and business operations. Because a simple BI tool fails to integrate advanced analytics into everyday workflows.
Here are the bottlenecks.
- The Disconnect between Data Science and Action
Findings from the data patterns and custom-built complex models remain trapped in notebooks and reports. There’s no definite infrastructure in traditional BI tools that seamlessly integrate these insights into the GTM team's workflow.
Such disconnection deprives GTM teams of valuable predictions like—
1. Lead scoring
2. Churn probability
3. Optimal pricing strategies, etc.
- Failing to Derive Value from Data Science, ML, and Predictive Analytics
All these advanced technologies help uncover deep insights, forecast future trends, and provide actionable recommendations. When compared to these technologies, BI exists in isolation:
However, extracting value from these insights can be challenging with conventional BI tools.
Impact: Your GTM team cannot boost revenue beyond a point as lack of modern tech halts strategic decision-making.
Marketers may fail to optimize marketing campaigns, identify customer segments, and personalize product recommendations. This results in reduced conversion rates, lower customer engagement, and missed revenue targets.
- Solution: Need for Next-Generation Analytics Platforms
These are designed to bridge the gap between data science and business operations. It can directly integrate into BI workflows through its range of sophisticated tools for data modeling, predictive analytics, and ML.
Impact: GTM teams can get comprehensive insights which helps proactive, data-driven decisions.
Here’s how the solution works
1. Operationalize ML Models: Deploying ML models directly into your BI environment makes predictions accessible in real-time through dashboards, reports, and alerts.
2. Automate Decision-Making: Data-driven insights pave the way for automated decisions triggered by predicting favorable outcomes. For instance, leads are automatically routed to suitable sales rep based on their predicted conversion likelihood.
- The Extra Step: Integrating Data Science into Your BI Ecosystem
Enable GTM teams to leverage data science by integrating it into your existing BI ecosystem.
This needs —
1. Data Preparation: Clean, structured, and accessible for both data science and BI purposes.
2. Model Deployment: ML models to integrate with BI platforms to make predictions available through dashboards and reports.
3. Workflow Integration: Connecting BI platform with CRM, marketing automation platform, and other tools to trigger automated actions based on data-driven insights.
5. Poor Performance When Data Comes from Multiple Disparate Sources
With BI, your data can remain scattered in silos.
The data lies across different sources – from CRM systems and marketing automation platforms to financial software and customer support tools. This poses challenges to BI performance and its overall efficiency.
It results in the following issues.
- Jumping Between Different Tools and Applications
GTM teams will need different applications and tools for different purposes. It happens because each tool is tailored to specific departmental needs. The downside is that such constant switching between applications creates delays and increases the risk of errors and inconsistencies.
Impact: Switching to different tools and apps for data can slow down decision-making processes and increase the risk of data misalignment. The hampered efficiency stems from wasting valuable time gathering data instead of analyzing it for decision-making.
It further leads to —
1. Inaccurate Insights: Data inconsistencies across different systems lead to inaccurate analysis and flawed conclusions, resulting in misguided strategies and missed opportunities.
2. Increased Costs: Manually managing disparate data sources is costly in terms of human resources and potential errors.
3. Limited Collaboration: Data silos create barriers between teams that hinder collaboration and prevent a holistic view of the customer journey.
Why Revlitix Is the Perfect Tool for Your GTM Team
As mentioned, you’d need to leverage the modern tech like AI and ML that fuels your GTM team. Revlitix can go beyond your generic BI tool by breaking down data silos, automating audits, and forecasting revenue.
Also, the seamless integration bridges the sales-marketing divide, providing early warnings on marketing and CRM data, and pipeline forecasting to reduce revenue surprises.
Here’s what Revlitix offers.
- Revlitix Reports
Integrate MarTech platforms by eliminating manual spreadsheet updates that allow GTM teams to set and track goals. Revlitix Reports is an AI-driven solution offering the necessary tools your GTM teams need to connect, forecast, and collaborate like never before.
It does do major things that your standard BI lacks.
1. Connecting KPIs
- Set clear goals for your marketing funnel and track real-time progress.
- Set up for ease of use, pre-built conditions help you track KPIs by importance and receive alerts based on trends.
- Streamline your reporting process and free up your team to focus on strategic initiatives.
2. Funnel Breakdown
Break down silos and foster collaboration across your GTM team.
A fully automated setup allows you to set custom goals for each funnel and track progress seamlessly.
Funnel Breakdown
Break down silos and foster collaboration across your GTM team.
A fully automated setup allows you to set custom goals for each funnel and track progress seamlessly.
Create metrics with clicks, not codes, and set custom goals for each funnel. Available for all KPIs, CRM, and MarTech stack.
- Revlitix Pipeline
BI tools can not predict the next impact your GTM teams are about to make.
But, Revlitix Pipeline can accurately forecast your pipeline — a game-changer for GTM teams that optimize marketing spend, and maximize your pipeline's potential.
Here’s how Revlitix Pipeline can transform your GTM strategy:
1. Unmatched Insights
- Uncover buyer patterns by Identifying the characteristics of your most successful customers to prioritize leads accordingly.
- Reduce time-to-revenue as your GTM teams can focus efforts on the activities and channels likely to generate revenue.
- Reduce the drop-opp in a funnel by understanding where leads fall off and implementing strategies to keep them engaged.
2. Predictive Analytics
- Leverage your data to generate accurate predictions for each stage of your funnel.
- Use tailored predictions to scale your spending confidently, knowing where to invest your next marketing dollars.
- Learn what is expected out of each funnel stage to hit your goals and predict performance against current targets.
Summing Up
We’ve seen how BI solutions fail to deliver timely, accurate, and actionable insights. As a result, your GTM teams can’t identify growth opportunities, fail to optimize marketing campaigns and improve sales effectiveness.
So, cutting a competitive SaaS space requires leveraging advanced analytics and AI that get you a competitive advantage. If your BI solution is falling short, your GTM team risks being left in the dust.
But, there’s a workaround — Revlitix.
Revlitix leverages AI to help GTM teams get all the info they need in one place, making their jobs easier and helping businesses grow.
Want to explore further?
