How to build a customer intelligence strategy in 7 Steps

AI & Customer Intelligence

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The best way to get data-driven insights about your current and prospective customers is to build a customer intelligence strategy for your business. Customer intelligence helps you better understand your customers so you can optimize their experience with your brand. 

Because this often involves a lot of customer data and information, the most effective way to collect, analyze, and act on this data is with the guidance of a customer intelligence strategy. 

In this article, we’ll share: 

  • What is customer intelligence?
  • How to build a customer intelligence strategy
  • How can the development of customer intelligence enhance relationship marketing with specific customers?
  • Using machine learning in your customer intelligence strategy 

What is customer intelligence?

Customer Intelligence is the process of gathering and analyzing customer data and using it to inform business decisions to improve the customer experience. This information comes from many customer interactions and sources, including survey data, purchase and account history, and interactions with your sales team or helpdesk. More robust customer intelligence strategies include an analysis of what customers are saying about your brand on publicly available third-party data sources like social media.  

Customer intelligence includes 4 phases:

  1. Strategy
  2. Data collection
  3. Analysis
  4. Action 

What is a customer intelligence platform?

A Customer Intelligence platform is a tool to gather and analyze customer feedback  in one place, making it easier to uncover meaningful insights using all available customer feedback data. It’s part of phase 3—the analysis stage of customer intelligence. 

There are various tools that first collect customer data, from customer behaviors, demographics, and feedback—whether it’s through your commerce platform, help center, customer surveys, or social media apps. Once the data has been gathered, the customer intelligence platform organizes and analyzes this data

Previously, companies would collect this data in spreadsheets for manual analysis. Modern strategy involves using a customer intelligence platform software that uses machine learning to analyze the collected data and look for trends and patterns. These are presented in the form of actionable insights that you can use to change business processes or product and service offerings to better meet your customers’ needs.  

What is effective customer intelligence?

Effective customer intelligence allows you to better understand your customers and informs ways to improve the customer experience and earn increased customer loyalty. This means:

  • Using ethical data collection: Gather data with permission or from publicly available sources (like public social media accounts) .
  • Collecting data from various sources: Collect data from multiple customer sources. Ideally, this should be a mix of customer-supplied information (eg: customer surveys), customer interactions (eg: chat bot conversations with the help desk), and third-party sources (like social media).
  • Maintaining customer confidentiality and privacy: When collecting and storing customer data, ensure you comply with all data confidentiality and privacy laws and ethics to prevent data breaches and leaking of customers’ private information. 
  • Collecting data throughout the customer journey: To get the fullest picture, collect data from various stages of the customer journey to see which need to be optimized to increase customer loyalty and increase your average customer lifetime value (CLV). 

How to build a customer intelligence strategy

Customer intelligence isn’t about collecting as much data as possible to find patterns. It involves building a strong customer intelligence strategy and executing it with your team. 

Here are the 7 steps to building a customer intelligence strategy:

1. Create your goals

Why are you doing customer intelligence? Knowing what you hope to achieve can help you create a strategy to meet your goals. For example, you may have found a low customer retention rate after 30 days and don’t know why. You can focus your data collection efforts on the customer experience between 1 and 60 days to see what correlations you may find. 

Based on the customer data collected, you may find people complain about the onboarding process and give up after a few weeks. This important insight tells you that your onboarding process needs a more customer-centric approach. 

2. Analyze data collection sources

What sources of data do you currently have? Make a list of all data sources, what stage of the customer journey they relate to, and which customer experiences or perspectives you need to know more about. For example: 

  • You may discover that you don’t collect enough customer-provided data after 6 months, so consider adding an automated survey to existing customers at the 9-month mark.
  • You may discover that you don’t have enough basic demographic data on your customers. You can add an extra one or two fields to your order forms or lead generation forms to collect this data. 
  • You may discover that you don’t have enough detail and historical data from customer support live chats on your website. You can correct this by adding an integration to sync chat data to your CRM. 

3. Vet and clean data sources

If you need to, clean your data sources before analyzing them. This is important to ensure that every brand interaction (purchase, email contact…etc) is linked to a specific customer account. This also means turning qualitative data (long answer survey answers) into quantitative data for easier tabulation or translating it into sentiment analysis. 

4. Choose a data analysis system 

Once you’ve collected the data, how will you analyze it? Manual data analysis is an option, but it’s very time and resource intensive. It also presents a higher likelihood of human error and misinterpretation. 

When you leverage a customer insights management and analysis platform you get faster and more meaningful insights, compared to manual human analysis. It eliminates the need for a full data science team to collect and review data. Instead, machine learning can accurately predict trends and present your marketing team with any red flags before they cause irreparable damage to your customer loyalty and brand reputation. Software like Idiomatic will uncover trends you may not have seen before and with data source integrations, your data and insights are always up to date.

5. Push vs. Pull data sharing

Decide how you plan to distribute data and insight from your customer intelligence platform. You can plan to push information to relevant teams as insights are uncovered. Or, it can be pulled when specific groups are looking for customer insights to answer a specific question or hypothesis. 

Ideally, if your resources allow, a good strategy will be a bit of both. For example, you have a data analysis team pushing data to your team members, but when they want answers to specific questions, you can provide them with the insights they need. 

6. Act on insights

How will you get the biggest return on your investment with customer intelligence data software? Use the analysis recommendations to better understand the voice of your customer so you can:

  • Create more timely product roadmaps
  • Inform future product and service update and releases
  • Change messaging and collateral to better meet your customer’s needs
  • Change customer support workflows
  • Evolve and improve your overall customer relationship management. 

A customer intelligence platform like Idiomatic can provide the actionable insights you need based on the data you collect on your customers. It can take various sources of quantitative and qualitative data and use machine learning to translate them into more accurate, actionable summaries and insights.

7. Monitor and repeat

Customer intelligence isn’t something you do once and never do again. It’s an iterative process of trial and error. Once you implement the changes your customer intelligence data suggests, give it time to ripple through your customer base and analyze again. With some customer intelligence software, you can get this information in real time without waiting. On-going monitoring will help you determine if your changes have increased customer satisfaction or if additional changes may be needed. 

If additional changes are needed, follow through with steps 4, 6, and 7 again to implement and test until you find the solution that works. 

How can the development of customer intelligence enhance relationship marketing with specific customers?

All data points can be linked back to a specific demographic when done correctly. You can look at specific insights based on any demographic data. For example:

  • Why are customers from Los Angeles only purchasing our cheapest subscription?
  • Why are women between 21 and 25 more likely to buy add-ons?
  • What demographic commonalities exist among those who cancel after one billing cycle?
  • Why are those with a $250K+ annual household income canceling our $19 per month product more than our $99 product? 

Creating a personalized experience 

Buyers expect personalization. According to an Epsilon and GBH Insights survey, 80% of respondents expect personalization from a brand. When you have detailed data points and behavioral data on specific customers, you can:

  • Create targeted ads and marketing based on what they need or are more likely to respond to. 
  • Offer rewards and incentives based on behavior. For example, you can send them specific emails like, “We noticed you’ve logged in every day for a month. Here’s a free gift.”
  • Create a different, tailored experience on your website based on their preferences. 

Using machine learning in your customer intelligence strategy

An AI platform like Idiomatic can help you uncover meaningful insights about your customers, which you can use to make changes to increase customer engagement and satisfaction. With Idiomatic, you can automatically feed your data sources into the platform and get real-time insights and actionable suggestions to improve the user experience. 

With the right software supporting your analytics, you can increase customer lifetime value, improve customer relationships, and get valuable insights to empower your teams to take action. 

Learn more about how Idiomatic’s customer intelligence software can be part of your strategy of analyzing customer data to better understand your customer. 

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