Best Practices

How to use data to drive better customer experiences | Census

Jesse Short
Jesse Short December 21, 2022

Jesse is a content strategist at Help Scout. After years of working in customer service and writing freelance, he made the switch to writing full-time and now spends most of his days writing about customer service and daydreaming about cheeseburgers and assorted pastries.

Almost every business on the planet is interested in improving its customer experience. And that’s for good reason: Increased access to tools and technology means that competition is growing in most industries. One of the best ways to stand out is by leveraging customer data as your competitive advantage. 💪

The desire to create excellent customer experiences is the first, and most important, step. However, without a data-driven strategy, you might find yourself struggling to figure out what works and what doesn’t. 🤷 Collecting customer data is just the beginning – you also have to make it usable and actionable for your business teams.

In this article, we’ll discuss how to unlock the potential of your data so you can improve your customer experience. 

Collecting customer data 

In order to use data to improve your customer experience, you need to collect it. Though there are potentially many different ways to collect data, there are two main types of customer data you can collect: Quantitative and qualitative

Quantitative data – sometimes called structured data – is generally expressed as a number. Things like customer satisfaction scores or net promoter scores are great examples of this. Basically, if you can chart it on a graph, it’s probably quantitative. 

Qualitative data – sometimes called unstructured data – is generally expressed in words rather than numbers. Things like customer interviews or text-based questions on a survey generate qualitative data. This type of data tends to be more anecdotal and less scientific. 

Both types of data can be very useful to help improve your customer experience on their own but are best used in conjunction with one another. 🤝 For example, you might have quantitative data from customers ranking potential new features to see what's most popular. Then, as a qualitative follow-up, you could chat with a couple of different customers to better understand exactly how they envision using the feature. 

After data collection, many companies often store their customer data in a data warehouse like Snowflake, Redshift, or BigQuery, or a data lake like Databricks. This creates a “single source of truth” for consistent reporting and ensures everyone across the organization has access to the same data. ⭐

Activating customer data to improve customer experiences

Storing data is essential, but making it actionable for customer success, sales, and marketing teams is even more important. What good is data if no one is using it?

Business teams talk to customers, answer emails, and send personalized campaigns every day. Their day-to-day operations can become even more efficient and informed with the right data at their fingertips. ✋

Let’s dive into some use cases where better data can lead to better customer experiences.

Building 360° views of customers

Customers interact with your brand in a variety of ways every single day. For example, they might visit your website, use your app, click on an ad, speak with a sales representative, or buy an item in a physical store. Connecting the dots and consolidating individual activities into a 360° customer profile is essential for understanding each customer.

Customer service is a great example of the potential of good data. When a ticket or request comes in, a support representative needs relevant information ASAP to resolve the issue. If their customer information is located in 5 different places, that slows down their response time and leaves the customer waiting. ⌚

Instead, if support teams have customer 360 profiles, they can see purchase data, billing data, and marketing interactions all in one place. They can immediately grasp the full picture of that customer’s interactions with their brand.

For example, if you use Help Scout as your customer experience platform, you can easily set up Customer Profiles that pop up alongside every request. A tool like Census will help you enrich profiles with interactions from outside Help Scout, so support representatives don’t need to leave the tool they’re familiar with to hunt down information.

Proactively building customer 360 profiles helps support teams resolve issues more quickly and deliver the best experience for your customers. 

Delivering answers faster and reducing friction

Friction is anything that causes your customer to put forth additional effort.

Did you know that around 70% of customers will try to find an answer to a question themselves prior to contacting support? That means that for most people, having to contact a support team already adds friction to the customer experience.

Customer behavioral data collected from your website, application, or product are great ways to find sources of friction in your customer journey. Product analytics tools like Mixpanel, Amplitude, PostHog, and Pendo can help you see if people are stopping on certain parts of your site or exiting the page after a specific action. You can see what kind of activity or what types of questions are most common for people at different stages of the customer journey.

Here are 2 ideas on how to make that data actionable 👇

  1. Proactive FAQ email: In Help Scout, you can add tags for things like customer industry and then run a report to see what types of questions are most common for that industry. Then, any time someone else from that same industry signs up, you can send them an FAQ email that anticipates their questions. Getting answers before you even ask is a pretty awesome experience. 
  2. Automated outreach for stuck users: Using Census, you can use friction points to trigger automated messages to move customers further along the journey. For example, if a customer looks at a product page for 10 minutes but doesn’t purchase, Census can send that data to your marketing tool and automatically enroll them in a personalized campaign.

Taking a proactive approach to support also reduces the number of requests that come into your support queue, improving life for your customers and your employees. 

Improving personalization at scale

We’re all inundated with a ton of different advertisements daily. 😵‍💫 With so much noise, people are less and less receptive to blanket sales pitches. These days, they’re looking for curated offerings that fit their wants and needs. In fact, research by McKinsey found 71% of consumers expect personalization

Trying to anticipate the needs of hundreds or thousands of customers can seem like a daunting task, but with the right tools, you can automate outreach that is personalized and efficient. 🏆

Use your customer data to power these use cases:

  • Abandoned cart follow-up: Send an email, text, or in-app notification asking if they’re still interested in their items. In fact, 45% of abandoned cart emails are opened, and 10% complete the purchase they originally abandoned. 
  • Upsells based on past purchases: Figure out what types of products are commonly purchased together. If someone buys just one but not others, you could send an automated follow-up suggesting the others.
  • Lookalike audiences: Analyze which types of customers have the highest CLV (customer lifetime value) and build segments similar to your best existing customers. Then use those lookalike audiences as a safe and cost-effective way to expand and improve the quality of your advertising audiences.

Every company does personalization to some extent, but automating your outreach and using better data results in huge differences in effectiveness and ROI.

A data platform like Census helps you make data actionable immediately. You can connect your data and your apps together to quickly make 360° customer information available in daily business tools like Help Scout, Salesforce, Iterable, or Facebook Ads.

The future is made of better customer experiences 🔮

Creating better customer experiences is certainly easier said than done. There’s no silver bullet that can guarantee success, but unlocking the potential of your customer data for action and automation will drive more revenue and create better overall customer interactions. 

So, be curious, ask questions, and make changes. When you take care of your customers, they’ll take care of you, too. 

🚀 Want to see how you can use Census reverse ETL to activate your customer data? Book a demo with a product specialist.

✅ And if you're looking for a better way to talk with your customers, check out Help Scout.

Related articles

Customer Stories
Built With Census Embedded: Labelbox Becomes Data Warehouse-Native
Built With Census Embedded: Labelbox Becomes Data Warehouse-Native

Every business’s best source of truth is in their cloud data warehouse. If you’re a SaaS provider, your customer’s best data is in their cloud data warehouse, too.

Best Practices
Keeping Data Private with the Composable CDP
Keeping Data Private with the Composable CDP

One of the benefits of composing your Customer Data Platform on your data warehouse is enforcing and maintaining strong controls over how, where, and to whom your data is exposed.

Product News
Sync data 100x faster on Snowflake with Census Live Syncs
Sync data 100x faster on Snowflake with Census Live Syncs

For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: