Today’s businesses are becoming more and more reliant on data to provide the insight they need to gain a competitive edge. Fortunately, today’s businesses have access to more data than ever before.
According to research by Statista, the average business organization uses more than a hundred different SaaS (Software-as-a-Service) applications. Many of these applications collect and store data that can reveal:
- Buying patterns
- Marketing trends
- Customer preferences
- Missed/emerging opportunities
- Campaign/content performance
This means that business leaders no longer struggle to find data, but rather, they struggle to leverage it to improve results.
This has led to the rise of marketing and sales analytics.
With marketing and sales analytics, businesses can use data to decode customer behavior and implement strategies to meet the demands of an increasingly discerning market.
If businesses want to compete in the information age, then they need to understand the importance of marketing and sales analytics and have the tools and strategies in place to use them.
In this article, we will explore marketing and sales analytics, outline some of the common challenges faced when trying to implement them, and provide insight into the tools and strategies that can help you get the most out of them.
What is marketing analytics?
Marketing analytics is the practice of collecting and analyzing marketing data in order to evaluate customer behavior and marketing campaign success.
These insights can help marketers improve efficiency and efficacy through:
- Improved forecasting
- Messaging personalization
- Better customer segmentation
- Customer journey optimization
- Marketing campaign refinement
Marketing analytics can help marketing professionals continuously streamline their marketing effectiveness, ultimately leading to better outcomes.
Additionally, good marketing analytics can help marketing leaders position proposals such as budget requests and campaign pitches, using up-to-date data to support their ideas.
What is sales analytics?
Sales analytics is the practice of collecting and analyzing sales data in order to evaluate customer behavior and sales success.
These insights can help sales reps close more deals, close deals faster, and increase upsell potential through:
- Enhanced messaging
- Improved forecasting
- Better customer targeting
- Refined lead scoring/assignment
Sales analytics can also provide sales leaders with data on sales activities and outcomes that can inform more effective sales strategies and tactics.
Additionally, sales analytics can be used to measure the performance of individual sales reps more accurately, enabling sales leaders to implement more effective sales incentive programs.
Analytics models
There are several models — or frameworks — that organizations use to derive meaningful insights from their data.
These models are the lens through which statistical information is viewed and guide the approach used to evaluate patterns, correlations, and predictions.
- The descriptive model- Descriptive analytics uses historical data to provide insights that will be used when determining future strategies and processes.
Essentially, this model looks at what worked (and what didn’t) in order to determine what an organization should focus on going forward.
- The diagnostic model- Diagnostic analytics uses historical data to provide insights into the underlying reasons for specific outcomes.
This model looks to uncover the root causes or factors that led to a particular result in order to prevent incorrect assumptions.
- The predictive model- Predictive analytics uses historical data to forecast future outcomes and trends.
This model uses various mathematical techniques to make predictions about customer behavior, potential sales revenue, and the success of upcoming campaigns.
- The prescriptive model- Like predictive analytics, prescriptive analytics uses historical data to make predictions about future outcomes. Where these two models differ is scope.
While predictive analytics seeks to make broad predictions about future outcomes, prescriptive analytics tries to identify specific strategies and approaches that will help achieve specific objectives.
Marketing analytics tools
There is a wide range of software tools available that support the gathering, analyzing, and communication of marketing analytics data.
- Web analytics tools- Web analytics tools can help businesses track and analyze website traffic such as page visits and click-throughs. This can provide insights into:
- User behavior
- Conversion data
- Website performance
- Content performance
- Social media analytics tools- Social media analytics tools track and analyze social media engagement and can provide insights into:
- Referral traffic
- Customer sentiment
- Content performance
- Influencer performance
- Customer demographics
- Marketing automation platforms- Marketing automation platforms provide tools and features that enable businesses to collect, analyze, and interpret data related to their marketing efforts. This can provide insights into:
- Lead generation
- Email campaign performance
- Affiliate/partner performance
- Social media campaign performance
These toolsets also provide advanced reporting capabilities and marketing campaign attribution models, both of which are very useful for communicating and understanding marketing analytics.
Sales analytics tools
There is a wide range of software tools available that support the gathering, analyzing, and communication of marketing analytics data.
- Sales engagement platforms- These tools are primarily used to aid sales teams in their prospecting and customer nurture efforts. That said, they collect data on email engagement, call activities, and other customer interactions, which can provide insights into:
- Lead quality
- Customer preferences
- Messaging performance
- Sales process efficiency
- Engagement effectiveness
- Lead management software- Lead management software helps businesses track, nurture, and convert leads into customers. The data these tools collect can provide insights into:
- Lead behavior
- Lead response time
- Lead conversion rates
- Lead scoring and segmentation effectiveness
- BI software- BI software (business intelligence) has in-depth data analysis capabilities and provides advanced data visualization features that enable businesses to create a variety of reports and dashboards.
While These tools do not gather sales analytics data directly, they can be very effective at providing insights and communicating results.
CRM is the best toolset for marketing and sales analytics
When it comes to marketing and sales analytics tools, nothing can compare to CRM’s (customer relationship management) ability to track both your marketing and sales efforts in order to provide you with the most complete and accurate picture possible.
This capability is enhanced through integration with other marketing and sales software tools and can provide you with a 360-degree view of the customer journey, allowing you to evaluate performance across your entire organization.
Plus, CRM reporting capabilities enable you to take all your data sets and visualize them into reports and dashboards that translate metrics into insights that everyone can understand.
The challenges of implementing marketing and sales analytics
There are many challenges that organizations encounter when trying to implement analytics effectively.
- Data capture and accessibility- Relevant data can come from a variety of sources, including:
- CRM platforms
- Market research
- Website analytics
- Advertising platforms
- E-commerce systems
- Customer communication channels
Ensuring that all relevant data is captured by these software tools is a big task and making it accessible to those who need it across departments and teams is another matter entirely.
Adding to this challenge is the fact that data collected from different sources can be inconsistent and prone to errors that are difficult and time-consuming to address.
- Technical expertise- Implementing analytics requires a team that understands and embraces data science.
Many marketing teams lack sufficient in-house talent to support their analytics efforts effectively and some organizations may even face resistance when adopting a data-driven strategy.
Changing mindsets and embracing data-driven decision-making may require organizational and cultural shifts.
- Communicating insights- Presenting complex analytical insights in a clear and understandable way can be challenging.
Team members, stakeholders, and decision-makers can become overwhelmed if the information presented is overly technical or relies heavily on industry-specific knowledge and expertise.
- Data privacy- When selling to businesses in industries like healthcare or Med Tech, privacy regulations such as GDPR and HIPAA add another layer of complexity to your marketing analytics efforts.
Compliance with data protection laws makes data accessibility challenging, especially if you don’t have the right software tools.
Our HIPAA-Compliant CRM Software Guide is a great resource for marketing teams looking to navigate the complexities of HIPAA compliance when collecting, storing, and accessing data.
FreeAgent CRM can help you take advantage of sales analytics
FreeAgent CRM is designed for today’s world of work and our robust toolset is ideally suited to supporting the varied work processes of modern businesses. FreeAgent is:
- Easy to use: FreeAgent works like you expect modern apps to work, providing a user experience that feels fresh and familiar. Teams love working in FreeAgent, leading to high adoption and greater ROI.
- User-configurable: FreeAgent can be configured by you to work the way you do. This means you don’t need outside support to add a form field, adjust a CRM automated workflow, or try out a new process.
- Customizable: With FreeAgent, apps, forms, and configurations are all completely customizable, allowing you to capture and connect your data in any way you like.
To see FreeAgent in action, get a demo, and discover for yourself how FreeAgent can help you have workdays full of impact.
