Customer analytics can be an invaluable source of insight for companies of all sizes.
Analyzing customers’ purchases, behaviors, engagement, and interests, then acting on that data in real time can lead to significantly improved business outcomes.
This is why so many mid-sized and large-scale organizations are investing in customer analytics technology to take their customer analytics maturity to the next level.
Historically, business intelligence (BI) tools, customer journey analytics software, and similar legacy technologies are commonly used for customer analytics.
However, many companies have substantial amounts of data across different systems, and these technologies are not designed to easily collect and unify that data for analysis.
This is why companies are turning to pure-play customer data platforms (CDP) with both predictive modeling and analytics capabilities like BlueConic.
It’s best to complement traditional customer analytics tools with a CDP that unifies all first-party data to enable more efficient and actionable analysis.
The evolution of customer analytics
The customer analytics technology landscape has evolved a lot in recent years.
To the point that business users without extensive analytics and data science backgrounds can model, analyze, and act on data. And all without heavily relying on the skills of dedicated analytics, business intelligence, and data science professionals.
It’s this democratized approach to customer analytics that has paid off for companies. Case in point: The use of customer analytics to inform marketing decision-making rose 21% from 2018 to 2019 for B2C businesses, per the CMO Council.
Of course, not all data-driven tools offer the capabilities teams need to better understand and act on customers’ buying habits, browsing behavior, product preferences, and the like.
Legacy databases like data lakes, MDM, and CRM are commonly used as single sources of truth for all big data. But robust customer analytics tools they are not.
Internal solutions that were once looked to for generating valuable customer insights (e.g., data warehouses) aren’t considered as valuable anymore. Why? Per Google analytics experts Robert Saxby and Saptarshi Mukherjee noted, their legacy infrastructure.
It takes a considerable amount of time and resources for IT and/or data science to glean worthwhile insights from a data warehouse. This data latency leads to ineffective, untimely data utilization for growth-focused teams — notably marketing.
Ultimately, this means technology decision-makers and team leaders must outline their companies’ unique analytics needs and pain points to find the best solution.
They understand the profound impact consented, first-party data — and rich insights based on that data — has on core business metrics: from customer loyalty to CLV.
This is another reason why so many are implementing a customer data platform to unify their data and simplify journey analysis for their teams. Not just those in analytics and marketing, but also ecommerce, customer experience, and even customer service.
The role of predictive customer analytics in companies’ success today
CDPs like BlueConic can enable you to not only look back at past prospect and customer data, but also predict future engagement and behavior.
As Forrester Senior Analyst Tina Moffett stated, artificial intelligence (AI) is now a critical business resource. And one that can play an important role in modern customer analysis.
According to Moffett, growth-focused teams — and, specifically, the leaders of these teams (CMOs, CDOs, etc.) “must embrace AI to achieve” success in their respective roles.
One facet of AI that can streamline customer analytics efforts? Machine learning technology that helps them develop and deploy predictive behavioral models. For instance, BlueConic offers out-of-the-box (OOTB) models any business user — regardless of technical expertise — can apply to their first-party customer data.
For instance, tech users on ecommerce teams can use our CDP to deploy one or more of our OOTB predictive models and determine when individual customers are likely to churn and/or buy next in order to more effectively personalize their experience.
Per a recent Gartner survey, many business pros — including and especially marketers — are starting to realize the benefits of predictive analytics. In fact, 80% of marketers plan to leverage predictive analytics in their engagement strategies moving forward.
Before they can, they must address two key challenges to improve their analytics maturity:
- 1) Improve their data literacy: That is, they must learn the ‘language’ of data so they can capably analyze and act on real-time customer insights.
- 2) Un-silo their customer data: In other words, connect all their existing systems and sources so data syncs seamlessly into a single source of truth.
The former can be accomplished by learning from their more technical counterparts in data science and analytics. The latter can be achieved by onboarding a CDP.
The ways in which you can improve your analytics maturity with a CDP
Data silos’ downsides have long been evident to organizations. (And, specifically, to C-suites.) As Entrepreneur contributor and marketing expert April Rassa astutely relayed:
- “Data silos have become the scourge of the 21st century. Besides the costs you’ll have to pay — because eventually you’ll have to undo this problem — separating data into various databases and programs rather than fully integrating it significantly hinders efficiency and productivity.”
Thankfully, ‘bridging’ data from different tools and syncing it into a single, readily accessible solution that democratizes data is easier than ever with a CDP like BlueConic.
Our CDP normalizes first-party data in a centralized location and creates persistent, dynamically updated profiles for each individual in a company’s database environment.
This enables every business team member who uses BlueConic to better understand their audience and efficiently assess and forecast their behaviors and actions. And all in real time.
Customers in various industries use our platform to analyze their customer base:
- Subscription-based businesses can predict which subscribers are most likely to churn so they can add them to a retention-focused program
- Publishing companies can determine what turns casual readers into new subscribers and entice repeat visitors to sign up for their newsletters
- Retailers can compare different buyer segments and identify ‘hot’ and ‘cold’ customers to know who to prioritize with their engagement efforts
From this analysis and resulting action, companies can realize greater ROI: both in terms of revenue generated and efficiencies gained across growth-focused teams.
No business professional becomes a customer analytics expert overnight.
But with the right processes and technology to support your customer analysis, you’ll be well on your way to better analyzing — and and acting on — your customer data.
Learn how you can improve your analytics maturity with BlueConic. Request a demo of our pure-play CDP today.