Marketing Analytics starts with your company’s vision and what it means for your employees as you identify what their day-to-day challenges are. The second phase consists of the collection piece. Taking a look at first, second and third party data and what is important to your organization that you need to collect in order to achieve a 360 customer view.
Thirdly, you must focus on how to take that data to transform it and analyze it on Google Cloud. You can opt for many different services like BigQuery, Dataprep, etc. to then implement use cases like machine learning, to ultimately visualize the data using products like Data studio, Looker, or other visualization tools. Lastly, you will be able to activate those insights in your day-to-day operations.
The ultimate goal of marketing analytics is to help organizations activate their data. Whether it be through delivering the right reports and dashboards to their executive team, objectives like reactivating an ads platform or use cases like content automation optimization and email marketing platforms.
Our current findings let us understand that organizations are experiencing the pain of data fragmentation.
Their data is spread across multiple platforms (data silos) resulting in lost opportunities. This phenomenon is noticeable throughout the data landscape; ad campaigns, CRM, customer service, logs, website, app analytics, billing and purchasing, point of sale, and many more.
The overwhelming feeling this fragmentation causes disables employees to extract insights from a singular source and renders any form of decision making based on the current view of your organizations’ customers impossible.
Without a more complete customer view, it’s really impossible to deliver the kind of relevant experiences that people expect today. We know that most companies are struggling with this problem. Forbes did a study in 2018 that found that only 13% of organizations say they’re making the most of their available customer data today.
Fobes Insights, 2018
And that’s what we are solving with our customers as Datasight. We’re bringing all of this data, that’s living in silos, into one place on Google cloud. By doing this, our vision is to create the leading cloud ecosystem for enterprises to extract better insights and get more value from their marketing and customer data faster.
So Datasight is supporting your customers’ business across the full data journey, providing your customers with the right tools they need to make the most out of their marketing data. Our solution is enabling Enterprises in every stage, from collecting your data, to transforming it with powerful cleanup tools.
Running analysis in seconds without server setup, visualizing it with dashboards and activating the insights drive better results. So it means that your customers will be able to manage the data lifecycle seamlessly, avoiding the need to Cobble together a bunch of different products.
And we’re making big investments in this area as well. And soon, we’ll be adding more data sets. More machine learning models, more activation connectors for you to bring to your customers. And what this really creates is a virtuous cycle that benefits the business by allowing your customers to always add more data sets.
As their data grows, applying more ML models, meaning better ways to activate their customer data, as well as better activations, which results in a continuous improvement of the cycle over time.
In order to help our customers to get started faster, we’ve developed a set of tools to help you accelerate project implementation by focusing on simple high value use cases. We based ourselves on our extended experience and the most common use cases we’re seeing in the market today.
These are the most common, but certainly the only ones we are able to help you with. Each of these use cases is designed to help connect and clean data sets in service of both short-term and long-term goals while minimizing the financial investment on your end.