A Basic Guide to Customer Interaction Analytics for Small and Medium Businesses

What could your business achieve if it had a better understanding of its customers? In a 2022 survey conducted by Gartner, 84 percent of customer service and service support leaders cited customer data and analytics as “very or extremely important” for achieving their organizational goals in 2023. For small or medium business (SMB) owners, these customer data insights are vital, but finding the time to manage all of them at scale—in addition to other critical business challenges—proves difficult.

As SMBs accelerate their business growth, increasing the customer base while improving customer retention requires a deep dive into the data. SMBs can use this to run analytics produce actionable insights that influence product development and special offers. This blog post will highlight the benefits of using customer interaction analytics, key tools that can help, and how some SMBs analyze customer data today.

What are customer interaction analytics?

Customer interaction analytics consolidate raw customer data collected across multiple channels into actionable insights. For instance, if you want to see how successful your webpages are at converting users, customer analytics can help. Other use cases include:

• Click data on an application
• Transactional data for product purchases
• Qualitative data from online reviews or customer support feedback

By unifying this information, SMBs can discover patterns in user behavior and unlock potential for new initiatives such as adjusting product features or targeted outreach to new markets. Simply put, it can help lead to a competitive advantage. At larger companies, there are dedicated data analysis teams who review this information on a regular basis and share findings with leadership. Traditionally, financial leaders have owned the domain of business analytics, but typically focused exclusively on profitability metrics.

Although SMBs such as yours may be under-staffed or lack technical talent, you do not need to be an engineer, data scientist, or developer to measure customer analytics. Customer behavior interaction data is often viewed on dashboards—or visual interpretations of raw data—with options to filter based on location, time, and other metrics. Anyone in your company whose role could be enriched with customer data analytics will be able to extract the insights they need to make smarter decisions without manually reviewing raw data.

A few benefits of SMBs using customer interaction analytics

If your company relies on anecdotal evidence or doesn’t know what it should measure, customer data analytics can help inform smarter business decisions. At Amazon Web Services, we lead with the following three benefits to help SMBs new to digital measurement:

Better understand your customers

Use customer interaction analytics to gain a deeper understanding of your overall user base, key demographics, and how they engage with different products and features. You can expand to new markets, industries, and locations by identifying those patterns and projecting usage forward. For instance, if you’re marketing a new service, you can see if there are any specific upticks in usage in a specific region and then further concentrate sales (and e-commerce) efforts to grow your business.

Recognize emerging business patterns

Finding patterns in user behavior helps SMBs make data-driven decisions for key business initiatives. By discovering broader themes in customer interactions, businesses can strategically build new products, update marketing messages, make smarter sales investments, and more. Additionally, observing usage patterns in end users across multiple channels reveals emerging themes in what’s garnering attention and where to innovate. For example, comparing negative call center data and website interactions over the same period of time might uncover website usability issues.

Move faster without manual analysis

SMBs can make agile decisions that in turn reduce time to market by having consolidated data available on demand instead of contracting with a third-party research firm. With customer experience data, business intelligence tools (such as dashboards) make it simple for SMBs to make decisions quickly. This accelerates product ideation, build-out, and time to market. If your SMB doesn’t build technical solutions, business intelligence can still help inform strategic investment decisions—especially during inflationary times.

What type of data can SMBs use to learn more about customers

Now that you understand why customer analytics are so important, let’s take a closer look at how to overcome the challenges that may prevent SMBs such as yours from implementing them. Common challenges are finding the right storage of disparate types of data, using self-service dashboards effectively, and analyzing data at scale using queries. The categories of data that help SMBs gain insights are:

• Structured data from enterprise systems: Examples include Customer Relationship Management (CRM) software, Enterprise Resource Planning (ERP) tools, and other databases. Larger SMBs typically have these available but they may not be synced together.
• Unstructured data such as text files, documents, images/video/audio: Regardless of size, most SMBs have a deluge of these files. Much of your company’s work occurs in these disconnected files but it shouldn’t discount their value.
• Semi-structured data such as e-mail and XML: Search and booking data from raw XML files can help identify low booking ratio for online travel businesses. Analyzing email content uncovers sentiment trends and patterns that can help improve customer retention.

Three challenges SMBs face with customer interaction analytics and suggested solutions

Challenge 1: What can I do with the disparate data my SMB is storing?

Organizations that successfully generate business value from their data will outperform their peers. As data storage needs increase, businesses are looking at scalable and cost-effective solutions to host their data. A data lake is a centralized storage that allows you to store all your structured and unstructured data at any scale. Data lakes store relational data from line of business applications, and non-relational data from mobile apps, IoT devices, and social media.

An Aberdeen survey saw organizations who implemented a data lake outperforming similar companies by 9 percent in organic revenue growth. These leaders were able to run new types of analytics like machine learning over new sources such as log files, data from website clicks, social media, and internet connected devices stored in the data lake. This helped them to identify and act upon opportunities for business growth faster by attracting and retaining customers, boosting productivity, proactively maintaining devices, and making informed decisions.

AWS LakeFormation easily creates secure data lakes, making data available for wide-ranging analytics. LakeFormation provides you the opportunity to improve operational efficiencies; centralize and democratize your data; and create and publish ad-hoc report.

Challenge 2: Are there easy to use, self-service tools to visualize data?

Cloud business intelligence tools help business decision makers create interactive dashboards, perform data visualization, detect patterns, and identify outliers in your data. Creating these dashboards can help aggregate many reports in one place by bringing together operational metrics from different departments.

Amazon QuickSight powers data-driven organizations with unified business intelligence. Take advantage of QuickSight dashboards to uncover hidden trends, recognize costs drivers, and improve forecasts in areas such as retail sale performance, manufacturing efficiency, and physician quality rating. If you’re one of the many SMBs interested in automation, scheduling reporting frequency is a great place to start. Ultimately, analytics tools such as QuickSight can help you unlock new opportunities and improve internal efficiency.

Challenge 3: What tools can I use to easily query and analyze data?

Self-service data analytics mechanisms such as full text search, real-time analytics, and machine learning help business owners uncover meaningful insights and generate predictions on their own.

Data Analytics on AWS offers purpose-built services that provide the best price-performance, scalability, and lowest cost. Using analytics at scale empowers businesses to interpret data from marketing campaigns, track content engagement, generate product pricing models based on past history, and improve customer acquisition strategies.

How one SMB utilizes analytics to better understand customer purchase intent

Mikatasa is a family-run business based in Indonesia that has been manufacturing paints and adhesives for more than 40 years. Their products have a reputation for high quality and can be found in more than 15,000 domestic retail outlets across the country. Mikatasa had a team of 30 members focusing on dealing with their backend tasks. By utilizing AWS fully-managed analytics services, they reduced the resources required for maintenance by 50 percent enabling them to focus on building front-end solutions for their customers. Moving to AWS Cloud helped lay out the foundation for retail data collection and analytics.

“We’re building layers and layers of information on top of raw data, and AWS provides us with the convenience of accessing that data, analyzing it, and facilitating information sharing,” said Martin Hendriadi Fu, Managing Director, Mikatasa.

This healthcare SMB connects its data sources to improve internal and external efficiencies

Healthvana is a US-based company that provides health records to patients on behalf of healthcare providers, including county and city agencies. Healthvana relies on multiple AWS services. Data analytics is vitally important to Healthvana’s products and their future growth.

On AWS, Healthvana has scaled its services to deliver over 35 million COVID-19 test results and COVID-19 vaccination records. Healthvana uses the Amazon Redshift data warehouse service to quickly generate critical customer health record reports. It also allows them to update their data warehouse in near-real-time. They are now able to send reports to customers, while also reducing the amount of time spent managing health record requests from first responders and healthcare workers. Internally, it helps them realize cost savings and accelerate innovation because less time is spent on low-value activities.

Next steps

By using customer data analytics, SMBs can gain valuable insights into their customers’ preferences, behavior patterns, and pain points. This can help them improve their products or services, personalize their marketing efforts, and ultimately increase customer satisfaction and loyalty, leading to higher revenue and growth opportunities. AWS provides the broadest selection of analytics services that fit all your data analytics needs and enables organizations of all sizes and industries to reinvent their business with data. Learn more about how you can leverage data analytics to make your business a smart business.