It may seem cliche, but the phrase “the more you know” is absolutely true when it comes to your customers. Because the more you know about your customers, the more your teams can make informed decisions that deliver a great customer experience.
Customer Intelligence is the process of gathering, analyzing, and then acting upon customer data in order to become more customer-centric. Furthermore, it involves understanding individual customers across channels at every single touchpoint along their journey.
With customer intelligence insights, your teams can deliver personalized information through the right channels at the right time with the right messages to optimize their experience.
But while customer intelligence in itself is significant, making it accessible and actionable to business teams is crucial. Without accessibility across teams, customer intelligence won’t have as great an impact on customer-facing operations. That’s why, to get the best results, your company needs a customer intelligence platform.
4 Common Types of Customer Intelligence Data
At a high level, customer data includes any information you collect about your customers.
In 2020, Domo estimated that every human created at least 1.7 MB of data per second, equating to 2.5 quintillion data bytes daily. And these are only digitally tracked totals.
Customer Intelligence data goes even further, tracking not only digital intelligence, but objective behaviors as well. Below are four categories of which customer intelligence data can be classified as.
1. Personal and/or Firmographic Data
All companies collect personal data on their customers and store it via a CRM system. From prospects to leads to customers, and everyone in between, likely a relationship has been tracked in the form of name, address, phone number, job title, and so on.
In a similar sense, B2B organizations collect firmographic data. This includes basic company information like annual revenue, industry type, location, business size, technologies used, and so on.
Both personal and firmographic data can be helpful alone for understanding the behavior of that individual customer. However, when this data is enriched with second and/or third-party data, it can build a demographic profile to help teams understand common attributes of current and future customers.
2. Engagement Data
Engagement data tracks all the different touchpoints of how your customer engages or interacts with your brand. Marketers and sales roles often utilize this data when referring to the buyer’s journey.
Common engagement data examples include number of program adoptions, social media engagements, website page views, social media “likes”, click rates, and so on.
From these insights, your team can optimize channel preferences and reach your customers when and through which channel they are likely to engage with your brand the most.
3. Behavioral Data
Behavioral data is very closely related to engagement data, but differs as it provides insight into why that customer behaved the way they did and tells the story of why they engaged with your touchpoint(s).
This data helps your team predict what your customers will do by analyzing how they behaved in the past. Do they prefer email communication over snail mail? Are they interacting with your business via their cell phone or laptop? Did they sign up for your recent campaign because of a tv ad?
In one example, Duquesne Light Company utilized CI to target customers most likely to need assistance programs. Because they understood their customer’s behaviors – at a household level – they were able to reach those customers with the right messaging to increase engagement 9 percentage points above industry benchmarks.
Behavioral data points can be granular. However, when combining this data across a spectrum of other customer behaviors, businesses can begin to create a story and understand the needs of their larger audience.
4. Attitudinal Data
Attitudinal data helps your team understand what the customer actually thinks about your brand and/or the solutions it provides. Some methods of collecting this data come in the form of interviews, reviews, support tickets, and/or satisfaction surveys.
Typically, this data is subjective and harder to assess. This is because not every customer shares their opinion about your brand, in the same way, or at the same volume. On the business side, without dedicated resources, it’s difficult to gather, track, and compile this data and make factual assumptions.
Simply having all this data doesn’t just bring about customer intelligence. Utilizing AI to find patterns in customer data attributes and segment customers accordingly, then engaging in strategic planning to decide how to operationalize CI, are crucial next steps.
As you can imagine, the more data you collect, the harder it can be to make sense of it all. This is why your business needs a customer intelligence platform. With it, you can harness the power of 360-degree customer views so your teams can make strategic decisions about their campaigns, content, programs, messaging, and more.
What is a Customer Intelligence Platform?
Simply put, a Customer Intelligence Platform (CIP) is a sophisticated system that collects all of the customer data listed above, linking billions of data points across disparate data sources, then unifies it to make it user-friendly and analysis-ready. It then serves business users across departments in sales, marketing, commerce, and service to access unparalleled customer insights to optimize customer engagement, surpass benchmarks, generate revenue, and achieve growth.
Why does your company need a Customer Intelligence Platform?
Businesses who choose to prioritize CX, according to Forbes, can experience an 80% increase in revenue. Data-driven decisions are based on facts, as opposed to spray and pray campaigns that can waste marketing dollars.
A CIP offers an opportunity to open up new revenue streams, helping businesses reach new markets, and reveals pathways to meaningful, targeted customer engagement.
Build Customer Experience Strategies
Personalization is key to CX and marketing success in 2022, and that isn’t likely to change anytime soon. Customer intelligence platforms make it easy (especially for smaller teams) to personalize outreach.
A customer intelligence platform will help your team make decisions with three key goals in mind:
- Know precisely where your best sources of revenue come from – so you can generate more of it.
- How to craft resonant, relevant messaging that meets your customers’ needs – so you sell more of your products or services.
- Where to look next to find more customers – just like the ones who bought into your product or service.
Remember, not every customer shares the same experience as the next. Demographics, income levels, and geographic locations, for instance, are major considerations to keep in mind when building your next campaign. Learn more about building a CX strategy with data here.
According to BlastPoint’s Jitendra Dahale, “data and data-driven intelligence is going to drive nearly every business decision.”
There’s so much data these days that, oftentimes, business teams don’t know where to start in organizing, gathering, or understanding what will bring them relevant insights. For some people, data overwhelms them and therefore gets pushed off to the side rather than utilizing it to make tasks more effective and efficient.
Having one platform for accessing customer intelligence makes it easier for non-technical/business teams to access and operationalize insights. Otherwise, data gets siloed within an organization and doesn’t offer much value to business teams.
That’s why targeted, specialized data is so important. Putting a purposeful framework around data provides specific answers to specific questions and, most importantly, gets results. Being strategic about the data you purchase also saves money, because data isn’t cheap.
Results or objective-driven segmentation is more effective than general, one-size-fits-all segmentation products. With all relevant datasets within one platform, users are able to create new segments oriented toward specific goals, providing better results.
For instance, Marketing teams can waste 50% of their ad spend experimenting with whether email, Facebook ads, or mobile alert campaigns will actually work to yield high engagement rates. With a CIP, they can aggregate channel preference data into their customer segments ahead of campaign launch to save themselves time and money by taking an objective-driven approach.
That’s because data provides them with the information of which customers should receive emails and which should see ads in their social feeds or via text message.
For example, American Electric Power utilized BlastPoint’s platform to decide how to launch their new chatbot. Thanks to BlastPoint’s AI-powered insights, they found that the customers they most wanted to utilize the chatbot were heavy Facebook users. In terms of demographics, they saw that a significant number of target chatbot users were single parents.
With these insights in hand, the CX team launched Facebook campaigns utilizing images and messaging that appealed to single parents. The results? A successful launch for the chatbot and Facebook engagement up to 30% above industry benchmarks. Learn more about this objective-driven segmentation story here.
Don’t let the more you know, slow you down. BlastPoint’s Customer Intelligence Platform makes it simple for business teams to turn customer data into results-driven customer AI.
Visit our case studies page to see more results we’ve helped companies achieve. Then, get in touch with our team to talk about how customer intelligence can help your team boost engagement and improve customer experience.