Google Cloud Platform: The Rainmaker

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It's time to move our analytics projects into the Google Cloud Platform. As a decision maker you'll need to have a clear plan on how to communicate the value your project brought to the business. This article will help you understand and articulate that value to a larger audience.  

Articulating the Value of Cloud Analytics Projects

In previous articles we've discussed the decision making that leads to moving your data onto the cloud and we've reviewed the technical details of BigQuery, the revolutionary, peta-scale data analytics platform. At this point you might be looking for signatures on your purchase-request-form. We want you to be successful, so we'll try to add value to your pitch by articulating the monetary benefits you gain by moving projects to the cloud.

Your customers like to be heard and feel loved

Most user experiences are optimized by analysts and decisions looking at data from a top-down perspective. I'm saying "top-down" in reference to the shape of that excel spreadsheet you are using for analysis. The top has your columns of metrics that you summarize looking down over the rows until you get to the bottom, where you find your KPI: Sum of Users who did <this>, Average time on page until <that> happened, etc... You can't possibly look at every single row in the data; but those are your customers. They are important and have unique needs that aren't always neatly aligned with the sums and averages of their peers. Your customers like to be heard and feel loved, and to do that you need to know your customers and make decisions based on that knowledge. Either you'll need to hire an army of sales and analytics team members to support this or we can deploy machine learning analytics, using the power of the Google Cloud Platform, to accomplish the task. We find value in the pivot from the "top-down" columnar perspective to "left-right", a customer-centric perspective. By making decisions from this perspective, treating each customer uniquely and serving experiences that satisfy and delight their needs, we're able to optimize your marketing strategies in ways that top-down strategies are not able to replicate. This pivot requires a massive increase in computational power. The difference between summing columns of data versus analyzing and modeling user scope clickstream and time series data is no small task. Advances in cloud infrastructure and technology products give marketing teams access to cutting edge technology at bargain basement prices.

The digitization of tools leads to the democratization of industry

Having access to the right tools to do your job is paramount to getting the most value from your projects. As we talked about previously, being able to optimize customer experiences using analysis of their own personal clickstream is computationally expensive. In order for your project to get funded you need to be able to demonstrate the return will be greater than the investment. If your IT or Data Warehouse Team is passing the cost of their expensive BI platform onto your marketing team then you'll often find that good ideas are left on the table because the math doesn't add up. The utility of a data warehouse as a tool to solve business challenges is diminished by adding layers of abstraction and bureaucracy. The creative minds are not able to place their hands on the control board and observe the outcome of their hypothesis. This is similar to musicians wanting to create a new album, only to be told by a studio executive that the studio time is too expensive and they'll need to delay recording until the pricing is more convenient to the budget. This problem was solved with GarageBand . Having access to a digital tool that does the work of an expensive studio meant the band could make the album of their dreams and skip the corporate bureaucracy in the process. Sounds like a win-win outcome for the band! To connect the metaphor back to marketing budgets, the Google Cloud Platform gives your team digital tools, that are easy to use, and just as powerful as the expensive data warehouse platforms that your IT team has surrounded with piles of change-management forms and processes. Lowering the barriers of entry will increase the frequency of new ideas. Giving these ideas legs, and infrastructure, at reasonable cost has incredible value. The return of an idea that never saw the light of day will always be zero. By democratizing access to cloud infrastructure, we add value by increasing the speed and frequency of projects and initiatives.

Crawl, walk, then run to a Data Driven Utopia

We have seen the value in shifting our processing power to the customer level, and also to know what it means to have the right tools for the job. Using the cloud for your marketing analytics projects gives you the runway to flight initiatives that would have otherwise never left the drawing board. The pay-to-use pricing model used by Google Cloud Platform allows for the infrastructure to scale proportionally to your effort. Modern business ethos demands you justify the ROI for a project before there is any chance for experimentation and analysis. This is because the platforms used to support marketing and business initiatives tend to be monolithic solutions. These bulky, rigid systems tend to not integrate with other solutions, and their pricing rarely allows for the phased, "crawl-walk-run" approach.  The nimbleness of the cloud, and pay-to-use pricing, allow your projects to scale according to the timeline that makes the most sense for your needs. We see incredible value in the cloud when trying to get new initiatives off the ground. As your programs mature, the gap between cloud and premise might shorten but now you have the data and evidence to justify the project expense when getting other stakeholders, like IT, involved.     Our experience is that as companies invest in cloud analytics, and give the marketing and data analytics teams room to experiment and take on new projects and initiatives, we see the data literacy of the entire company increase. Having a thoughtful approach to collecting data ensures accuracy and reporting, dashboarding and visualizations help to increase awareness and trust of the data. We are left with a self-repeating feedback loop that steadily advances the culture of the company toward a data driven ethos; we like to call this place Utopia.  

Conclusion

Deciding to move to your analytics operations to the cloud can be a daunting challenge. I hope this article has framed the value of this move in new ways that you hadn't otherwise considered. We know at the end of the day our goal is to execute our marketing strategies using the best information available. Red-tape and other organizational challenges might make it harder for you to accomplish your goals but there are other alternatives and they're easier to use than you might think. At Analytics Pros, our team is experienced with using the Google Cloud Platform to give digital marketers the tools they need to accomplish their job. In the process we find our clients to be the heroes of their organization, bring value in ways executives never thought were possible. We want to help get "machine learning" off the front page of Wired magazine, and into the fabric of your digital user experiences. Reach out to us and continue the conversation from our contact us page or on our twitter, @AnalyticsPros. Looking forward to hearing about your challenges in conveying value to your company leadership for your analytics initiatives!