What is Data Activation? 4 Steps to Making Better Decisions

With the explosion of digital technologies, companies are vacuuming up massive amounts of data about consumers’ online and offline behaviors. Such data is harnessed by businesses to make strategic decisions, drive business intelligence and build new products.

For example, an e-commerce firm that wants to figure out which marketing channel is the most profitable must combine data from HubSpot (marketing automation), Facebook and Google Ads (advertising), Shopify (e-commerce website), and Stripe (payment gateway). However, bringing various data sets together from disparate sources seamlessly and in real-time, is extremely difficult. As a result, it isn’t easy to realize the actual value of data.

For a long time, modern data-driven companies have been using ETL to create data warehouses as central repositories. With this data in hand, data and business analysts get to utilize it and deliver their insights to respective departments, such as the customer success team.

Your customer success team wants to prioritize which support ticket they should target first. To do this, the customer success team wants high-quality, trustworthy data in near real-time in the tools they use to resolve support tickets effectively.

Putting your data to operational use is an essential step. You can put the correct data straight into your customer support teams’ tools daily by data activation. This will help you save time, minimize duplication, and transfer your data from your warehouse to the location where it’s put to daily operational use.

It helps democratize your warehouse’s data so that non-technical teams can utilize it in applications like HubSpot or Salesforce. This helps eliminate the barriers between the business users and data teams and thus completes the data loop.

With this thought in mind, it becomes vital for all organizations to activate their data. 

The question is, where do I begin?

In this article, you’ll find out what a successful data activation framework looks like and how to build and manage one for your team.

What is Data Activation?

Currently, most companies use ETL pipelines for data integration into data warehouses. Business teams then use this data to create reports and provide analytics solutions. But the time consumed in developing these reports causes delays in providing up-to-date insights to the operational teams, which usually leads to delays in taking action and doesn’t make the data as helpful as possible.

Activating your data is the need of the hour to get real-time data and make data actionable.

Data activation is the concept of extracting value from data by developing insights and putting those insights into action. In other words, data activation is one of the methods through which marketers leverage valuable data and consumer insights to improve the customer experience across all marketing channels.

Data activation attempts to provide a complete picture of the consumer to inform and improve customer experiences across all marketing and advertising operations. Robust and scalable marketing data solutions are required to capture, store, and analyze digital interactions accurately and seamlessly. 

Data activation necessitates real-time data collection across all digital channels and devices. The capacity to develop outstanding customer experiences is accelerated by real-time data analysis.

A Practical Example of Data Activation

Let us understand data activation through a real-life example.

Assume you work as a customer service representative for a rapidly expanding technology business. You handle inbound support requests in Intercom, your company’s helpdesk, and assist customers in resolving their difficulties.

Because your organization is quickly expanding, there is a rising amount of requests to resolve. Your manager has determined that tickets should be prioritized based on churn risk rather than chronological order (first in, first out) (i.e., the higher the churn risk, the higher the priority). According to the manager’s beliefs, this is a superior method of preventing churn.

Your organization’s churn risk is assessed using a combination of data such as product usage, most recent invoices paid, number of support inquiries in the previous 30 days, and NPS score.

This looks complicated without data activation. When you receive a ticket, you check up on the company’s product use statistics in your PostgreSQL database. You go to Stripe to get invoice data, Intercom to view the number of support tickets, and AskNicely to see their most recent NPS score.

At best, you could have pre-calculated health score models in a BI tool or spreadsheet to help with this procedure. Overall, depending on the consumer, this procedure might take anywhere from 30 seconds to 10 minutes. And the tickets in your Intercom mailbox are still building up, waiting to be handled.

Furthermore, without data activation, this data merely informs the decision-making process, implying that you must return to Intercom and make an active decision on which support issue to address first.

In the presence of data activation tools, your whole process becomes entirely different. The health score model is pre-built and resides in your data warehouse, which houses your client data. It syncs with the Intercom immediately and refreshes every minute. Support tickets are automatically prioritized in Intercom based on that metric, without you having to do anything.

As you can see, data activation dramatically transforms the use of data by automatically converting insights into action. That is where the true power of data activation lies.

The Present State of Data Activation

From the example above, you might have understood how beneficial it is to activate your data. 

Still, many businesses rely on business reports or dashboards – some try to activate their data by manually writing against third-party APIs using in-house scripts.

They would write their API connections from the data warehouse to SaaS products to stream data into operational platforms like Salesforce, Marketo, HubSpot, etc. Because endpoints may be fragile and most APIs are not designed to handle real-time data transfer, teams must implement batching to bypass rate constraints. It might take time to map fields from the data warehouse to the SaaS solution. This manual method of creating APIs consumes a lot of bandwidth, and it might be challenging to maintain the connections over time. As a result of these pressing issues, reverse ETL solutions have evolved.

Sure, we can’t deny that developing an indigenous reverse ETL solution might help you better adapt your solution to your firm’s use case and demands. However, customizing your reverse ETL solution can become cumbersome and requires extensive analysis of your current business processes.

You may be apprehensive, but investing large sums of money and time developing a reverse ETL solution would be a foolish attempt, given that equivalent functionality is available, at significantly lesser costs, if you buy reverse ETL solutions for activating your business data.

With the help of automated reverse ETL platforms, you can allow your employees to get accurate and timely data inside the applications they use. In other words, users can avoid switching between applications to obtain more specific information and have confidence in their data, making it more actionable.

How do Cross-Functional Teams Benefit From Data Activation?

The data warehouse has long been the go-to solution for the data silo problem. This data integrated into the warehouse does not sync between platforms and is either unusable or difficult to obtain.

Surprisingly, the data warehouse eventually developed the same issues as a data silo. Due to inaccessibility, data that had been retrieved, converted, and put into a warehouse, lake, or lakehouse has become stagnant. This has created a new concern for firms, not allowing company-wide access to data across different data and business teams.

With the advancement in technology, such as reverse ETL, you can activate your data that helps you to tackle the data silos problems by making it simple for businesses to share their data warehouse insights or provide a single view of their customers across various departments inside the organization.

This implies that instead of each team developing their own definitions (Lifetime Value, Health Score, Active User, and so on), these metrics are defined once in the data warehouse and shared across all tools used by all teams in the business. It helps to break down data silos and get the entire organization on the same page.

With the help of a single view of all the customers, companies are experiencing tremendous advantages like:

• Pushing data from the data warehouse to Salesforce allows them to maintain an up-to-date list of high lifetime value clients or customers that spend more than $1500 per month. 
• By providing tailored messages that incorporate product metrics, companies are able to mirror product use data in their Intercom. They can then work on enhancing customer interactions.
• Syncing internal customer data into Zendesk helps them save time while responding to support inquiries and automatically prioritize messages as they arrive.

How Data Activation Maturity is a Competitive Differentiator?

According to a study by Forrester, B2B marketers and sellers make 48 percent of their decisions on intuition or personal/company experience rather than quantitative data and analysis. 

By activating their data using reverse ETL platforms, companies can gain a competitive edge over their competitors. Through data activation, they can get real-time data into their daily used applications such as Salesforce, Hubspot, etc., to make judgments such as properly attributing marketing performance or improving and crafting engaging customizing experiences.

They are also more likely to claim improvements in important marketing, sales, and customer KPIs such as sales cycle speed, return on marketing investment, and customer loyalty.

How does Data Activation Work in Different Sectors?

Data Activation in Sales

By activating data, the sales team can use the CRM lead score to prioritize leads in Salesforce or Hubspot.

How Figma is Enhancing Its Sales Productivity by Activating Customer’s Data

Figma is a cloud-based collaborative design platform that allows you to build anything, including websites, apps, and logos. Figma was facing a lot of challenges before data activation. They had to:

• Identify and route freemium customers with high-income potential who would meet Figma’s ICPs (based on product use).
• Create a unified account hierarchy model to provide their account executives with a 360° perspective of the company.
• Create a customer health score (using product data) to identify accounts with high potential or that are in danger.

By activating their data, they were able to overcome these challenges:

• The sales team’s productivity increased when all product data was made available and unwrapped in Salesforce.
• They were able to identify upsell possibilities from current accounts.
• Within Salesforce, their sales team was able to see how each client was using their product.

Data Activation in Marketing

By activating data, marketing teams may construct hyper-targeted email marketing campaigns by segmenting consumers using criteria such as Customer Acquisition Cost (CAC), health score, or Monthly Recurring Cost (MRR).

How Bleach London Reduced Their CPA by 20% Using Data Activation

Bleach London provides hair coloring, bleaching solutions, and related items. After the COVID pandemic, Bleach London changed its business strategy to increase its top line. They had complex segmentation in their BigQuery database and new customers were being added daily, but they required that data to sync instantaneously to Facebook Ads. They wanted to refill the seed audience rather than relying on a static upload, which has to be done repeatedly.

By activating their data using a modern reverse ETL platform, they solved their problems by getting near real-time insights into Facebook Ads. They were also able to achieve a lot of targets:

• Improve email open and conversion rates with more tailored product suggestions based on purchase history.
• Save an entire workday every month by managing audiences in a single location on top of the warehouse and synchronizing them to both Facebook Ads and Klaviyo.
• Enable self-service data access for teams to quickly construct segments and assess effectiveness across multiple campaigns.

Data Activation in Customer Support/Success

With the help of data activation, support teams’ inbound tickets can be automatically sorted by priority order based on the health score measure. Here’s an example to explain how Bold Penguin was able to achieve low latency support.

How Bold Penguin Improved Customer Support Times From 24 Hours to 30 Minutes

Bold Penguin is an insurtech firm that provides services to commercial insurance carriers and agents. They give a quotation platform in conjunction with a retail insurance market to assist brokers in matching firms with “the proper quote in record speed.” 

Bold Penguin was facing the following challenges:

• Maintaining bespoke scripts was time-consuming and diverted valuable BI resources away from other projects.
• Business users typically had to request updates from data teams to acquire the most up-to-date analytics in their preferred tool.
• Teams were held down by manual processing of data, such as manually identifying client categories in Intercom.

By deploying reverse ETL technologies, Bold Penguin’s Customer Success team was able to achieve top-notch client satisfaction by detecting and addressing issues in near real-time. Reverse ETL also notified them about agent terminal problems. 

With these recent advancements, 

• Support response time for partner issues has been reduced from days to minutes.
• Bold Penguin can now allow business analysts who are not part of the BI team to build up their own data connections.
• Marketing segmentation has become an automated process that enables marketing and sales teams to focus on targeted efforts.

4 Steps to Effectively Activate Your Data and Empower Decision-Making

Data Foundation: Building Rich Views of Customers

The first stage of data activation is gathering data from different sources and transferring it to a consolidated platform inside a single framework. Here, data from multiple sources, such as websites, mobile applications, offline databases, CRM systems, media mentions, or transactional data, may be used in aggregation.

Decision-making: Analyzing Data to Take Action

Once all data has been collected in one location to generate a full image of the client, analytics can be performed on the data. This may be utilized to drive outbound marketing promotion and optimization and uncover new consumers who fit the target profile. Some examples are audience analysis, attitude analysis, act-alike modeling, and data modeling.

Design: Crafting Right Offers, Messages, and Experiences at Speed

The next stage is to put the data activation insights into action. This phase comprises extensive integrations throughout the ad and marketing ecosystem and the exchange of data segments generated with marketing partners.

Distribution: Delivering Experiences Across Platforms

The last stage of data activation is assessing the effectiveness of data activation techniques. Practice and refinement guarantee high performance, and outcomes are as exact as feasible.

The Faster & Easier Way to Activate Your Data: Reverse ETL

Data activation using reverse ETL opens up a slew of possibilities. Data may be readily synchronized to any destination using reverse ETL. After enriching all the data in your warehouse, you may put your data back to work.

• Data Enrichment: You can now exchange and exploit your behavioral data with numerous data and marketing destinations such as Salesforce, Hubspot, and Marketo. For example, you’ll be able to customize your marketing campaigns in your Email Service Provider (for example, Braze) based on the goods a customer viewed while browsing your website.
• Better Audiences: With reverse ETL, audiences may now be presented with more detailed behavioral cues. An example would be a cart abandonment audience that syncs to Facebook, Google, and your Email Service Provider (ESP) for multichannel retargeting marketing. You no longer have to worry about building and sustaining each audience across numerous places, but instead, create them centrally using reverse ETL platforms. In a nutshell, richer audiences are centrally controlled and enabled throughout your stack.
• Resource Savings: You can outsource integrations and API administration using a reverse ETL solution. This lets your technical staff concentrate on high-value tasks – what is essential to your company rather than managing data infrastructure or integrations with third-party systems.

How to Implement Data Activation Framework Using Hevo Activate?

Hevo’s no-code data activations make it simple to replicate data from your data warehouse to a target business application. You can even modify your data replication procedure during the Activation creation process by selecting appropriate sync behaviors.

An activation connects data from your warehouse to the target object. Each run of the data activation goes through the three processes of identifying records from the data warehouse, transforming them, and loading them to the target. It is a four-step process:

• Step 1: Select your data warehouse source.
• Step 2: Specify your target destination.
• Step 3: Select the data you want to sync by writing SQL queries.
• Step 4: Map your warehouse fields to your target fields.

How Ebury Builds Reliable Data Products Using Hevo Activate

Ebury is a global fintech firm that uses modern data technologies to improve and automate financial services and processes for small and medium-sized enterprises (SMEs) that trade and transact globally.

Ebury helps such companies in removing transactional barriers associated with more traditional methods. Ebury’s entire business verticals, from sales to core platform products, rely on data to perform well. It must also comply with the regulatory regulations of numerous geographies since it operates worldwide and processes financial data from approximately 49,000 firms across the globe.

Using Hevo Activate, Ebury achieved near real-time data replication by sending insights from Looker to Salesforce with automatic schema detection and 100 percent data accuracy. Not only this, but Hevo Activate has also contributed to boosting team collaboration and improving data reliability.

“With Hevo, our data is more reliable than before. Hevo allows us to build complex pipelines with ease and after factoring in the excellent customer service and reverse ETL functionality, it is undoubtedly the best solution available in the market.”

– Juan Ramos, Analytics Engineer, Ebury

Final Words

To reduce data silos, data warehouses were established. However, for many businesses, data warehouses have devolved into data silos. Reverse ETL tackles this problem by lowering the barrier between a data warehouse and the rest of the organization. Teams can operationalize data in systems and processes they are familiar with and act on it to generate outcomes.

In today’s fast-paced data economy, reverse ETL delivers data to the hands and workflows that require it and when they require it.

People are still confused about whether Data Pipeline and reverse ETL should be considered a single space. Many discussions have been about whether reverse ETL is a new product or feature. Still, we all agree that it’s adding considerable value to data teams and data-driven organizations. It enables teams to leverage the data to the maximum by making it accessible across organizations and actionable in daily operations. 

As a category in the cloud data environment, reverse ETL might have started as a distinct offering as different companies have started building the product. 

But in the future, you might see vendors offering bi-directional data pipelines, i.e., ETL/ELT and reverse ETL on the same platform. Since ETL/ELT and reverse ETL are a part of the same platform because the product users and the requirements are the same, i.e., to manage data flow within the data stack and move data to and from the data warehouse. 

With a bi-directional data pipeline, the gap between data, insights, and user productivity is eliminated, which is the need of the hour and the key to closing the modern data stack loop.