Intercom to Snowflake – Made Easy
If you’ve come here, you are probably looking for a way to transfer data from Intercom to Snowflake quickly. In this article, we talk about why Intercom is essential and how you can get access to this data without having to write any code.
The typical buying journey of a customer is no longer linear. They will switch between websites, compare similar products, search Google for promo codes, drift to trusted online sources for reviews, before returning to your website and finally making a purchase; perhaps using a completely different device. Thus, eCommerce vendors have to decide on what channels they want to sell and how much to spend. Understand customer demand and problems play a critical role in the success or any business. Customer service is one of the best ways to gauge the pulse of the customer as you get feedback directly from the people buying your product or service.
An excellent Customer Service:
- Increases the number of loyal customers who visit repeatedly
- The loyal customer base is more open to viewing more products and trying out new ones, increasing how often they purchase from you.
- Increases the amount of money each returning customer spends with your business.
- Loyal customers generate positive word-of-mouth about your business and provide testimonials and reviews, which help organically increase new visitors.
- Ensures a minimum recurring revenue, decreased marketing budgets for customer retention, and increased budgets for new customer acquisition resulting in sustainable growth for the business.
Today, customer service is not limited to the traditional telephone support agent. Customers have a variety of media to interact with businesses like WhatsApp and other IM services, Social media platforms, Emails, Chat systems on your website along with phone and SMS. Many companies also offer self-service support, so customers can, to an extent, find their answers at any time of day or night.
Companies with the best customer support system
- Track every move of their customers
- Have sophisticated chatbots or IVR systems installed to keep customers engaged before, and the actual operator can attend the issue. Studies have shown that the most frustrating thing people have claimed when it comes to customer service long waiting times, and most people lose their patience and this ultimately results in the issue remaining unresolved and customers losing faith in the brand.
- Listen and reply to complaints on social media and emails; this creates an image of a brand that cares about its customers.
- Ask for regular feedback, reviews, and suggestions from the customers to gain insights into their experience with your brand even if they are not complaining or reporting things.
- Provide support based on the activity of the customer like browsing habits, exciting products, response to marketing activities, and provide tailor-made guidance to them to influence them in buying a product or a service.
Ensuring optimal customer service requires constant monitoring of the customer service team, customer queries, and feedback. Hence, it involves manually generating reports from multiple data silos and analyzing them, which is where most brands falter. This compiling is a daunting task in itself, as it takes time to prepare all these reports which are then analyzed. This time-lag is one of the biggest challenges that companies face.
Data Savvy eCommerce businesses try to reduce the effort of reporting and analysis by integrating data from all these channels into a cloud data warehouse like Snowflake. By taking this step, the process of reporting and analysis becomes easy, inexpensive, and consequently done more frequently.
In this post, we will be looking at methods to replicate data from Intercom to Snowflake.
Before we start explaining the process involved in data transfer, let us know more about the individual platforms separately.
Intercom helps to deliver modern, on-scale business messaging. It empowers users to create stronger customer relationships with flexible messaging that offers a more personal experience. Intercom facilitates Lead Generation, Customer Engagement, and Customer Support. Intercom is designed to provide everything teams need to provide each customer with customized experiences — consistently and on a scale. Some of the powerful features are:
- Business Messenger – Support action and decisions with chat, engaging apps, conversational bots, and product tours.
- Management tools – Develop multichannel customer interactions at scale with reporting, collaborative inboxes, and automated workflows.
- Customer data platform – Aim, customize, and summarize every interaction from across the stack with behavioural and consumer data.
- Apps and integrations – Automate conversational behaviour, synchronize data between tools, and link to an existing tech stack with over 100 pre-built apps and integrations, a flexible API, and free workspaces for developers.
Snowflake is a cloud-based data warehouse created by three data warehousing experts at Oracle Corporation in 2012. Snowflake Computing, the vendor behind the Snowflake Cloud Data Warehouse product, raised over $400 million over the past eight years and acquired thousands of customers. One might wonder if another data warehouse vendor is needed in an already crowded field of traditional data warehousing technologies like Oracle, Teradata, SQL Server, and cloud data warehouses like Amazon Redshift and Google BigQuery. Well, the answer is the disruption caused by cloud technologies and cloud opportunities for new technology companies. Public clouds enabled startups to shed past baggage, learn from the past, challenge the status quo, and take a fresh look at cloud opportunities to create a new data warehouse product. You can read this article to understand the core technology components that make up this modern, cloud-built data warehouse for consumers of cloud technologies.
You can register for a $400 free trial of Snowflake within minutes. This credit is sufficient to store a terabyte of data and run a small data warehouse environment for a few days.
Why Do Businesses Need to Replicate Intercom to Snowflake?
Let’s take a simple example to illustrate why data consolidation from Intercom to Snowflake can be helpful for an eCommerce business.
An e-commerce company is selling in multiple countries, across different platforms and marketplaces, for example, its website, Amazon and eBay. The company needs to have the following information in real-time.
- How many customers were upset?
- How many customers left with a positive impression after the assistance?
- How many of these customers churned?
- Are high priority customer service tickets being addressed on time?
- Is a high-value customer treated the same as a medium-low value customer?
- Is the team efficient with resolving issues?
- Are issues being addressed on time?
- Has the CLTV increased with improved customer service if not, then why?
Now, the different sources of customer feedback maybe through Intercom, responses from emails, Reviews, and ratings on Amazon & eBay, SMS, phone calls, social media sites. So different data silos are being created per feedback source, per country. Compiling all of this data together is necessary to get a clear picture of the business, but it is a daunting task in itself, and it takes time to prepare reports which are then analyzed. This time lag that occurs is one of the biggest challenges that companies face since it delays the decision-making process.
Because of the lack of timely data, companies fail to address critical points like :
- Identifying whether the training of the customer service team is proper or further training is required
- Whether the Customer Service team is understaffed and needs reinforcing.
- What should be the ideal frequency of monitoring the team and creating reports?
- What type of customers is raising more tickets?
- What are the most common issues in customer feedback analysis? Is it a technical problem or a vendor fault?
- Is it necessary to handle customers with specific problems, or High-value customers, uniquely or differently?
Thus companies that use a chat support platform like Intercom typically feed all of the data coming from it and all other apps and tools to a data warehouse like Snowflake for easier and faster analytics.
Replicate data from Intercom to Snowflake
There are two board ways to pull data from any source to any destination. The decision is always a build vs buy decision. Let us look at both these options to see which option provides the business with a scalable, reliable, and cost-effective solution for reporting and analysis of Intercom data. You can also retrieve the data from Snowflake any time you want. To know more, click here.
Use a cloud data pipeline
Building support for APIs is not only tedious but it is also extremely time-consuming, difficult, and expensive. Engaging analysts or developers in writing support for these APIs takes away their time from more revenue-generating endeavors. Leveraging a cloud data pipeline like Daton significantly simplifies and accelerates the time it takes to build automated reporting. Daton supports automated extraction and loading of Intercom data into cloud data warehouses like Google BigQuery, Snowflake, Amazon Redshift, and Oracle Autonomous DB.
Configuring data replication on Daton on only takes a minute and a few clicks. Analysts do not have to write any code or manage any infrastructure but yet can still get access to their Intercom data in a few hours. Any new data is generated is automatically replicated to the data warehouse without any manual intervention.
Daton supports replication from Intercom to a cloud data warehouse of your choice, including Snowflake. Daton’s simple and easy to use interface allows analysts and developers to use UI elements to configure data replication from Intercom data into Snowflake. Daton takes care of
- rate limits,
- historical data load,
- incremental data load,
- table creation,
- table deletion,
- table reloads,
- refreshing access tokens,
and many more important functions that are required to enable analysts to focus on analysis rather than worry about the data that is delivered for analysis.
Daton – The Data Replication Superhero
Daton is a fully-managed, cloud data pipeline that seamlessly extracts relevant data from many data sources for consolidation into a data warehouse of your choice for more effective analysis. The best part analysts and developers can put Daton into action without the need to write any code.
Here are more reasons to explore Daton:
- Support for 100+ data sources – In addition to Intercom, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms, and much more. Daton will ensure that you have a way to bring any data to Snowflake and generate relevant insights.
- Robust scheduling options allow users to schedule jobs based on their requirements using simple configuration steps.
- Support for all major cloud data warehouses including Google BigQuery, Snowflake, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL, and more.
- Low Effort & Zero Maintenance – Daton automatically takes care of all the data replication processes and infrastructure once you sign up for a Daton account and configure the data sources. There is no infrastructure to manage or no code to write.
- Flexible loading options allows to you optimize data loading behavior to maximize storage utilization and also easy querying.
- Enterprise-grade encryption gives your peace of mind
- Data consistency guarantee and an incredibly friendly customer support team ensure you can leave the data engineering to Daton and focus instead of analysis and insights!
- Enterprise-grade data pipeline at an unbeatable price to help every business become data-driven. Get started with a single integration today for just $10 and scale up as your demands increase.
Interested in learning more about data warehouses, their architecture, and how they are priced? Check out our other articles.
|Google BigQuery||Google Bigquery Pricing Google BigQuery – Architecture and Key Features|
|Snowflake||Pros and Cons of Snowflake Snowflake Architecture|
|AWS Redshift||Amazon Redshift|
|Oracle Autonomous DB||Oracles Autonomous Data Warehouse|
|For sections where we talk about manual reports and lost productivity||https://sarasanalytics.com/blog/improving-data-analyst-productivity|
|What is a cloud data pipeline||https://sarasanalytics.com/blog/what-is-a-data-pipeline|