Building a Marketing Analytics Stack With DataChannel And AWS Redshift
Every day, business organizations, both large and small, are burdened with tons of data on consumer choices. Information related to clicks, impressions, unique visitors, etc. do help businesses a lot, but then again, sometimes it fails to translate into better decisions. That's why interpreting data is where the herculean task lies. For that reason, Business experts and marketers use analytics these days to make smarter decisions.
In this article, we’ll be going in depth into what marketing analytics is and how to integrate marketing data into an AWS Redshift warehouse, with DataChannel.
What is marketing analytics?
Marketing analytics is the practice of perusing metrics data to determine if inputs are commiserated with returns. It takes a closer look into the ROI of marketing efforts like Channel performance, calls-to-action (CTAs), blog posts, etc. While also identifying opportunities for improvement by tracking and reporting on business performance data, diagnostic metrics, and leading indicator metrics.
With the aforementioned, marketers provide answers to analytical questions that are of paramount importance to their stakeholders. The marketing analytics stack tries to make difficult processes easier. It equally measures the impact of marketing activities and drives more efficient spending.
If you can correctly measure your marketing efforts, you would be able to make smarter business decisions, acquire more customers, and drive significant growth in your business. That’s to say, with strategic marketing, every business manager stands a greater chance of making strategic marketing decisions, thereby competing favorably in the new digital data era.
Before now, marketers traditionally depended on the siloed or manual reporting methods. But the stress and unreliability involved with these techniques has been enormous.
Let’s examine the Siloed and manual techniques.
Siloed reporting technique: Usually, marketing reporting tools are meant to offer industry specified solutions, primarily-importing data, and visualizing such data in one application. This is done in siloes, where you can only view data from one source at a time. There are several reporting tools out there in the open to help create marketing reports. They treat data from different platforms separately.
You can create a separate Facebook report, google Analytics report, and AdWords report in this light. The challenge here is that they can’t be integrated to get an all-inclusive report that will aggregate cost data from AdWords and revenue data from Google Analytics.
Monitoring the number of conversions completed; you will only know about ads from a specific platform. You can’t get a comprehensive report on the performance of all advertising channels used in your campaign. For this reason, some marketers resort to manual reporting to make up for this.
Manual reporting technique: Marketers who are data-driven tend to assess their marketing efforts from customer relationship management(CRM) and analytics coupled with some other back-end systems. Copying and pasting data into a spreadsheet can be quite complacent. The manual reporting technique has been noted to be strenuous and time-consuming.
This technique is prone to errors, as large amounts of data are imported from various data sources. This error is only spotted when you do the reporting, which happens only once a week. By then, you lose out on many optimizations and corrective action opportunities. As businesses gain traction, the size of data that needs to be stored, monitored, and analyzed expands exponentially.
With traditional database warehouses, queries will start taking more time, making data difficult to manage. You would realize that this technique is no longer sustainable, especially if you have to keep track of several markets, websites, or brands.
Hence, marketers need to build an automated and flexible marketing reporting stack using the best of breed components. The objective is to ensure all data is always available and up-to-date. With the rise of cloud computing, the need for warehousing solutions that can scale up for the increasing demands of data storage and analysis has been apparent, resulting in organizations looking for alternatives to traditional on-premise warehousing. There are three layers to a modern marketing reporting stack. They include:
Data import platform- Most marketing data exists in third party advertising and marketing platforms. Getting the data into a data warehouse involves integrating with and maintaining a large number of APIs. A single tool or a combination of tools can be used to handle this.
Data warehouse- data warehouse is a highly scalable data repository used for reporting and data analysis. New cloud-based offerings from Google and Amazon have made data warehouses available to the mass market with self-service offerings and affordable pay-as-you-go pricing.
Finally, data access & visualization are finding a tool to access and analyze all of these marketing data imported.
Now, you have the freedom to identify with a particular tool to solve the entire problem of data integration or use multi-combined tools to import all your data into the warehouse. All thanks to the arrival of AWS Redshift and the DataChannel as a direct response to this demand. With the proficient help of just AWS Redshift, you can automate your tasks and not just monitor your database but also scale it.
However, you would still need a cloud platform to integrate all your data under one single data warehouse extensively, and for that, DataChannel is there for you. Keeping your data safely stored under one cloud platform with automated permission, accessibility, and scalability features open for you.
You may wonder, how do these all work together? Let’s quickly look at them in brief.
AWS Redshift: This is a Cloud-based data warehouse product designed for large scale data set storage and analysis. With it, it means all of your mundane administrative tasks are catered for. Redshift automates all your Administrative tasks. It is a column-oriented database management system. The information is in columns, and because of this, it can be analyzed far more quickly, unlike other applications that store data as rows.
Redshift’s column-oriented database connects to SQL-based clients and business intelligence tools, making data available to users in real-time. Based on PostgreSQL 8, Redshift delivers fast performance and efficient querying that help teams make sound business analyses and decisions. It doesn’t end there; with it, you can equally scale your data.
Redshift has the capacity to scale up to petabytes but gives you the freedom to start with just a few gigabytes of data. Leveraging Redshift, you can use your data to acquire new business insights. It is reputable for its speed. The speed by which Redshift processes large amounts of data is impossible to attain with traditional data warehousing, making it the top choice for applications that run massive amounts of queries on-demand.
DataChannel: which could easily be referred to as data management, is an integrator. It collates data so that marketers can see a picture of the fundamental whole instead of seeing them in bits. As mentioned before now, the DataChannel is an open-source cloud platform that enables you to integrate all your data under one single data warehouse extensively.
The platform allows you to integrate all the fragmented pieces of data collected from your diverse marketing channels and safely stores them in a huge centralized data warehouse where you can access them as and when you require them. Data generated across platforms like CRM, analytics, marketing, research, customer orientation, commerce, and more are rapidly increasing. Here, DataChannel steps in to play a major role – it collects the granules across all platforms and finally collates all your data together for easier access.
Why use DataChannel with AWS Redshift?
With the DataChannel, you have the most comprehensive data integration technology, set up in minutes without any coding, or long scripts. You can directly connect your AWS Redshift, which is a cloud-based data warehouse and analytics service run by AWS, Amazon Web Services, the cloud-computing department of the tech giant which will in turn extensively integrate all your data under one single data warehouse with automated permission, accessibility, and scalability features open for you. Why use BlueVenn with Amazon Redshift?
With Datachannel integrated with Amazon Redshift, you no longer need to rely on data analysts to access and make sense of your data. In fact, DataChannel turns your marketers into analysts through its marketer-friendly data visualization and analytical tools.
Benefits of DataChannel integration with Amazon Redshift include:
Super-fast data access – By using Amazon Redshift’s columnar storage technology, you gain unparalleled speed and fast query performance.
Ease of use for marketers –DataChannel-friendly drag & drop user interface ensures that complex data can be analyzed and made actionable with little or no training.
Robust security – Strict security measures are built into both DataChannel and Amazon Redshift, giving you the peace of mind that every byte of your customer data is safe and secure.
Limitless insights – Through its speed and ease of use, DataChannel allows marketers to query data without limits. This makes segmentation, and the creation of marketing campaign lists more accurate and targeted.
Providing you with actionable insight
When integrated with Amazon Redshift, Datachannel enables marketers to get full access to all their data.
DataChannel provides analytical tools to make sense of the data. Through a suite of marketing automation tools, marketers can activate the data into highly-personalized multi-channel marketing campaigns that drive interaction and boost sales.
Having each of your data unified and stored under a cloud platform with the most powerful data integration engine and the fastest, doubling as the anchor. Entrusted with the ability to monitor and analyze all your diverse loads of information from all data sources, including AWS Redshift. Hence, giving a prompt insight into the impact of each of the business marketing tools adopted.
With a robust marketing reporting stack in place, you now have the ability to build but automate much of your marketing reporting and make timely analysis you could not support with silos and spreadsheets.
Are you set to explore and discover hidden insights embedded in your data?
How to move data to Redshift using DataChannel
-Select your Data Source
-Freely choose from our list of pre-defined sources or request a data source if we do not have it in our library
-Connect your Data Source to us
-Connecting your data source is as easy as authorizing access and selecting the data you would like to sync
-Customize your needs
-You can schedule when and how much data you want to sync, choose the granularity and breakdowns – all at the click of a button
-Put your data to work
With Standardized schema coupled with easy access, you can start using your data right away.