Marketing analytics: Why you need a modern data warehouse

A cloud-based data warehouse is your shortcut to superior marketing analytics and a 360-degree view of your customers.
February 23, 2021

With the vast number of brand choices presented to consumers today, customer loyalty can be elusive. But the more you know about your customers and their buying motives, the more you can anticipate their needs and influence their purchase decisions. To do that, you need to collect and analyze a lot of data on your customers — data that’s typically stored in line-of-business applications across your company.

Salesforce, NetSuite, Zendesk, Shopify, Asana and thousands of other applications each contain data on your customers. Some of that data is shared across applications, and some is unique to individual applications. When you aggregate and analyze such varied data, you get what is known as a customer 360 view, which allows you to better serve your customers and grow your relationships with them — and generate more revenue.

With the business climate and customer demand more unpredictable than ever thanks to Covid-19, you need to generate actionable insights that let your company change course on a dime. And while there are several ways to access the requisite data, each approach has its pros and cons.

Centralizing your data is key to better insights

One of the simplest ways is to use the built-in dashboard in your marketing technology (martech) tool, like the ones in Marketo or Salesforce. These tools are easy to use and will always be a part of your daily workflow, but they don’t give you a complete view of your customer. Some of the business data that’s critical to your marketing strategy and decision-making process may not live in your martech tool — social media engagement data, for example, or customer service metrics from a tool like Zendesk. To access that data, you’ll need another tool, such as a turnkey business intelligence (BI) dashboard like Domo, which connects directly to your data sources.

These BI tools contain many built-in connectors, so they can give you a more complete view of your customer, but they are limited to analyses that were anticipated by the creators of the tool. The day will come when you have a question that your turnkey dashboard can't answer.

Building your own data warehouse from all the critical data sources within your company is an effective way to get the data needed to make business-critical decisions. While it will require more upfront investment than a typical martech tool or turnkey dashboard, it will allow you to leverage data from multiple sources and answer any question about your customers.

Fast, reliable data is a competitive advantage

To get the most out of data in today’s world, you need a data warehouse that can handle the three V’s of big data: volume, variety and velocity. More specifically, the technology must be able to store millions of pieces of data from multiple — and frequently changing — data sources. And these sources need to be updated in close to real time to ensure you’re making the most accurate decisions possible.

All this means that your data warehouse must be fast. To support the kind of exploration that goes hand in hand with modern analytics, it must be able to answer a new question against all existing data in just a few seconds — not minutes or hours.

The systems that meet all these requirements are cloud-based data warehouses, such as Snowflake, BigQuery and Redshift. And they all have an ecosystem of partners that integrate your marketing data quickly and easily.

Making the right choice for your data warehouse can have a major impact on your marketing efforts and the growth of your company. With the ever-growing need for fast and accurate answers from analytics, the technology you choose matters.

A version of this blog post was originally published on Forbes Tech Council.

Kostenlos starten

Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Data insights
Data insights

Marketing analytics: Why you need a modern data warehouse

Marketing analytics: Why you need a modern data warehouse

February 23, 2021
February 23, 2021
Marketing analytics: Why you need a modern data warehouse
A cloud-based data warehouse is your shortcut to superior marketing analytics and a 360-degree view of your customers.

With the vast number of brand choices presented to consumers today, customer loyalty can be elusive. But the more you know about your customers and their buying motives, the more you can anticipate their needs and influence their purchase decisions. To do that, you need to collect and analyze a lot of data on your customers — data that’s typically stored in line-of-business applications across your company.

Salesforce, NetSuite, Zendesk, Shopify, Asana and thousands of other applications each contain data on your customers. Some of that data is shared across applications, and some is unique to individual applications. When you aggregate and analyze such varied data, you get what is known as a customer 360 view, which allows you to better serve your customers and grow your relationships with them — and generate more revenue.

With the business climate and customer demand more unpredictable than ever thanks to Covid-19, you need to generate actionable insights that let your company change course on a dime. And while there are several ways to access the requisite data, each approach has its pros and cons.

Centralizing your data is key to better insights

One of the simplest ways is to use the built-in dashboard in your marketing technology (martech) tool, like the ones in Marketo or Salesforce. These tools are easy to use and will always be a part of your daily workflow, but they don’t give you a complete view of your customer. Some of the business data that’s critical to your marketing strategy and decision-making process may not live in your martech tool — social media engagement data, for example, or customer service metrics from a tool like Zendesk. To access that data, you’ll need another tool, such as a turnkey business intelligence (BI) dashboard like Domo, which connects directly to your data sources.

These BI tools contain many built-in connectors, so they can give you a more complete view of your customer, but they are limited to analyses that were anticipated by the creators of the tool. The day will come when you have a question that your turnkey dashboard can't answer.

Building your own data warehouse from all the critical data sources within your company is an effective way to get the data needed to make business-critical decisions. While it will require more upfront investment than a typical martech tool or turnkey dashboard, it will allow you to leverage data from multiple sources and answer any question about your customers.

Fast, reliable data is a competitive advantage

To get the most out of data in today’s world, you need a data warehouse that can handle the three V’s of big data: volume, variety and velocity. More specifically, the technology must be able to store millions of pieces of data from multiple — and frequently changing — data sources. And these sources need to be updated in close to real time to ensure you’re making the most accurate decisions possible.

All this means that your data warehouse must be fast. To support the kind of exploration that goes hand in hand with modern analytics, it must be able to answer a new question against all existing data in just a few seconds — not minutes or hours.

The systems that meet all these requirements are cloud-based data warehouses, such as Snowflake, BigQuery and Redshift. And they all have an ecosystem of partners that integrate your marketing data quickly and easily.

Making the right choice for your data warehouse can have a major impact on your marketing efforts and the growth of your company. With the ever-growing need for fast and accurate answers from analytics, the technology you choose matters.

A version of this blog post was originally published on Forbes Tech Council.

Topics
No items found.
Share

Verwandte Beiträge

No items found.
No items found.
Fivetran Product Update: October 2024
Blog

Fivetran Product Update: October 2024

Beitrag lesen
Data governance is a top priority for AI success
Blog

Data governance is a top priority for AI success

Beitrag lesen
Build vs. buy for AI: Choosing the right data foundation
Blog

Build vs. buy for AI: Choosing the right data foundation

Beitrag lesen

Kostenlos starten

Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.