Companies collect data all the time and it is called “big data.” Big data can help companies understand their customers better and make smarter choices. For managed service providers (MSPs), software tools that analyze big data are becoming super important. These tools help MSPs serve their clients and grow their businesses.
This article will look at how big data tools are changing the role of MSP software. You’ll learn how data analytics helps MSPs work smarter.
The Critical Role of Big Data Analytics in MSP Business Strategy
To get a competitive edge, MSPs need to anticipate customer needs before they’re obvious. That’s where big data analytics is vital.
The market potential is skyrocketing too. The big data analytics industry is expected to reach a valuation of over $655 billion by 2029, up from $241 billion in 2021, highlighting its critical role in modern business strategy.
Leveraging Predictive Analysis for Proactive Growth
With the exponential growth of data, analyzing historical trends has become essential for forecasting future customer needs. As the volume of data heads towards 181 zettabytes by 2025, predictive analysis allows MSPs to stay ahead of the curve when it comes to understanding evolving customer expectations.
By monitoring previous service usage patterns and industry shifts, MSPs can predict challenges that customers might face in the future. This foresight allows them to make data-driven decisions to launch relevant new solutions even before issues arise, delighting customers with proactive value-added services.
Several MSPs are already reaping rewards with predictive analysis. For instance, Hughes increased service sales by 15% in the first year through predictive modeling. CompuQuip was able to predict potential cash flow issues months ahead by analyzing historical financial data combined with market trends, allowing them to take preventive steps and ensure steady growth. These success stories underline the transformative impact predictive analysis can have.
Identifying and Capitalizing on Market Trends Through Big Data
The key to sustainable growth is identifying significant market trends and evolving customer needs early. Here too, big data analytics proves indispensable.
With the business intelligence and analytics software industry valued over billions, MSPs must take advantage of these powerful tools. Techniques like exploratory customer analytics and statistical modeling can uncover hidden correlations and trends in data that humans cannot easily detect.
Here is a table comparing the traditional approach versus using big data analytics:
| Traditional Approach | Big Data Analytics Approach | |
| Method | Relying on gut instinct and limited customer feedback | Using statistical modeling and exploratory analytics on large volumes of data |
| Identification of Trends and Needs | Slower to detect emerging trends and changing customer needs | Rapidly uncover hidden correlations and trends through advanced analytics |
| Adaptation to Market | Slower to align offerings based on trends | Data-driven agility to quickly tailor offerings to emerging needs |
| Outcome | Hit-or-miss relevance to customers; slower growth | Highly relevant offerings that closely match customer needs; faster growth |
As the table shows, big data analytics allows MSPs to spot trends and adapt faster.
Capital One is one example of creative trend spotting with big data. By analyzing the shopping habits of card customers, they identified growth in specific product segments like specialty pet goods. Aligning partnerships and offerings accordingly resulted in a 10x lift in relevant purchase volumes.
Likewise, MSPs can leverage analytics to spot upcoming technology and security needs of SMBs even before they materialize, allowing rapid alignment of additional solutions. This data-driven agility results in relevance, retention, and revenue.
Data-Driven Strategies for MSP Optimization
While analytics uncovers crucial insights, acting on them is equally vital. This requires strategic planning and operational changes guided by data.
As MSPs advance beyond basic IT support to integrated service providers with advanced analytics offerings, they can leverage these capabilities internally too for greater optimization. MSP software solutions offer integrated data analytics capabilities that can help drive this transformation.
From forecasting staffing needs by geography based on historical ticket volumes to optimizing field technician routes using demand heat maps, data touches all aspects of MSP operations. Support times have been slashed drastically by using predictive analytics to plan resource allocation for incoming calls during high volume periods, achieving near-perfect service level adherence.
ConvergeOne increased its asset and configuration database accuracy from 60% to 95% by combining and analyzing discordant data from various monitoring and billing systems. This eliminated redundancies and asset sous-utilization, saving over $250,000 in annual costs. Annual IT asset depreciation write-offs were also right-sized based on actual expected life from analytics, generating additional tax savings.
TechnomaIT was able to identify nearly $45K in annual cost savings by analyzing historical infrastructure utilization patterns and right-sizing cloud subscriptions accordingly. The savings continue adding up!
Upselling and Cross-Selling: A Data-Driven Approach
Besides cost savings, optimized business analytics presents lucrative upsell and cross-sell opportunities too, especially in MSP ecosystems with integrated solutions. By analyzing historical buying patterns coupled with propensity models, MSPs can identify customers primed for additional sales and the right solutions to offer.
For instance, analyzing support tickets and recent security threats revealed a surge in multi-factor authentication requests for a customer segment at Cetan Corp. An integrated cross-sell promotion resulted in a 37% conversion rate for its new two-form authentication solution from those accounts.
Likewise, TechnomaIT increased QoS upgrade upsells by over 20% the previous quarter by targeting customers facing bandwidth issues revealed through historical utilization data analysis. The numbers speak for themselves when it comes to data-driven selling!
Financial Optimization Through Big Data Analytics
For MSPs, accurate predictive modeling using historical financial data combined with market trends has proved invaluable for steadier cash flows and expenditure optimization.
By analyzing past billing and revenue data, billing errors or process bottlenecks can be identified and eliminated to prevent future leakages. Common trends like seasonal oscillation in cash flows can also be forecasted to better plan budgets or staffing needs. MSP software company, Accelo, saves over $200,000 annually through insights gained from historical data-driven budget planning.
Data analytics thus empowers both strategic cost savings plus opportunities for growth, perfectly poising MSPs in today’s dynamic business landscape.
Enhancing Operational Efficiency with Accessible Data
To fully harness the power of analytics, having readily accessible high-quality data is imperative. However, disparate systems and siloed repositories pose a challenge for most MSPs. Integrated business analytics solutions address this by providing a single version of truth.
Standardized reporting and centralized data access dashboards have proved tremendously beneficial in connecting departments and systems. They eliminate duplicate data entry, minimize manual reporting needs, and provide transparency between technicians, sales teams, and leadership by establishing centralized data access protocols.
Studies show that MSPs with connected analytics tools demonstrate over 14% faster issue resolution rates and 18% higher technician productivity. This underscores the critical nature of accessible analytics for daily coordination as well as long-term planning.
Strategic Decision-Making with High-Quality Data
Ultimately, the biggest advantage MSPs gain from big data and analytics is enhanced decision-making capabilities. By tracking various operational and service parameters over time coupled with emerging market trends, leadership can base difficult strategic choices on hard reliable insights rather than guesses.
SolarWinds MSP was able to identify the optimal sales incentives during seasonal slumps by testing out variations derived from historical market data. This resulted in a 32% increase in sales conversions year-over-year for targeted subscriber segments during typically slow quarters. Quality data delivers quantifiable results!
FAQs
What specific benefits does big data analytics offer MSPs regarding customer retention and satisfaction?
Predictive analytics allows MSPs to identify issues proactively and launch relevant solutions even before customers face problems. By delighting them with timely value-added offerings aligned to emerging needs, customer retention and satisfaction increase tremendously. Data-driven insights help cement enduring customer relationships.
What are some key challenges MSPs face in big data analytics adoption and how can they overcome them?
Many MSPs struggle with data quality issues, integration complexities across systems, and a lack of in-house skills for managing large data pipelines. Starting with limited PoC projects, extensive staff training programs, and consultant partnerships helps build knowledge and confidence for enterprise-wide analytics implementation over time.
Can smaller MSPs effectively use big data analytics? What are good initial starting points?
Even smaller MSPs can benefit greatly from basic analytics like dashboard reporting for business insights. Dedicated analytics modules within PSA or RMM tools offer plug-and-play analytics without extensive investments. As requirements advance over time, larger standalone analytics platforms can be evaluated. Starting small allows building capacity gradually.
