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February 03, 2017

By Vignesh Clingam SVP, Decision Sciences at RAPP Dallas

Cloud-based analytic platforms are driving automation and improving the predictive accuracy of marketing programs across organizations. While Big Data and cloud platforms have disrupted data warehousing and storage tech over last decade, they are now driving disruption across the marketing function in many industries. Cloud-based analytic platforms can solve some the key challenges that daunt marketers like connecting data, reporting, insights gathering, decision making and optimizing marketing programs.

In 2014, Gartner hype cycle report assessed that Big Data trend was entering a ‘trough of disillusionment’ after its explosive growth over past few years. The following year Gartner removed Big Data as an emerging technology trend, citing the fact that it has become prevalent in our lives, and hence is no longer an emerging trend. Yet, in a recent report McKinsey claims that less than 30% of the value of data is being captured across industries and applications of big data will continue growing, as its true potential is yet to be fully tapped.

For many organizations, these trends may sound familiar given their large investments in enterprise datawarehousing and IT platform migrations, yet their impact on making better decisions or increasing the speed of decision making seems very minimal, if any.

Shifting to the cloud isn’t a set-it-and-forget-it proposition. It still comes down to the quality of your data — and your ability to gain insights from it. Cloud-based analytics platforms can’t solve data gaps or fix corrupt data. They can’t correct measurement errors or tell you which metrics to focus on. All of that still comes from you and your team.

Instead, these platforms allow you to measure and track KPIs, and to continually speed the gathering and reporting of whatever metrics you choose to track. From a marketing perspective the key benefits of cloud-analytics are centered around:

  • Real-time optimization. 
By tracking customers, orders, or sales in real time, you can finally get away from those weekly or monthly KPI reports. Rather than waiting for the end of the month to set strategy, you can pivot your marketing execution almost daily, on the basis of up-to-date performance metrics. Instead of looking at past performance and tweaking future execution — with a big-time lag in between — you can finally start to optimize the present.
  • Real-time personalization. 
By tracking customer engagement across channels at the time of transaction, you can also serve up the right content, experiences, or media impressions to the right person at the right time — and through the proper medium, as well.

In the past, such personalization was driven by A/B testing, which can take weeks to find the perfect combination of message, offer, and call to action necessary for conversion. With cloud-based analytic platforms, such large-scale tests can be run constantly, allowing you to apply your insights without delays.

  • Real-time scoring.
Marketing organizations spend considerable time and effort building predictive models for campaigns. But with changing customer behaviors and the volumetric data challenges, it’s often not feasible to update and deploy these static models in a timely manner. By leveraging cloud-based modeling tools, you can make predictive models run constantly in the background. At any given time, the entire customer database is scored with all available data. You can access the information necessary to predict how consumers will respond to a given message and then adjust accordingly.

And with 86 percent of companies reporting increases in ROI through predictive marketing, cloud-based analytics platforms are not something to consider on your roadmap a year from now, but essential to compete in the new normal today.

While speed, modernization, and simplicity of use are all important, one objective ranks higher for more than 47 percent of IT departments in large organizations: cutting costs. In fact, moving from static reporting to cloud-based solutions can lead to significant cost savings for most teams. While marketing teams are eager to adopt cloud-based analytics to drive better insights and results, for IT teams the key imperative is to reduce cost and overhead across the enterprise. We see rapid migration and adoption of such systems, when marketing and IT teams work together to realize the benefits of better agility and lower cost, rather than work against each other – in many cases due to organizational mis-alignment or lack of clarity on end-benefits to business.

In addition to reducing overhead and cost, cloud-based analytics also drives democratization of data within organizations. KPIs and insights that were bound in spreadsheets and reports can now be accessed by anyone in your organization to unlock value. Such platforms can often be the key to breaking down silos among marketing, sales, operations, finance, and other teams within your company.

Take Finish Line, for example. The athletic apparel retailer combines online and offline data to better understand the touchpoints with its customers. By gathering and tracking everything from beacons and loyalty data to point-of-sale and social streams, Finish Line personalizes its interactions with consumers to not only convert, but also upsell.

Use the power of the cloud to apply insights to market faster than your competition. In a 2015 survey, 57 percent of organizations saw improvements in decision-making after executing cloud analytics, with even greater improvement in collaboration and response time to customer requests.

Predictive analytics using real-time data connects marketing with sales, links operations with management, and even shows the company where to build its next stores. When properly utilized, it has the potential to drive transformational change across the enterprise.

For organizations looking to drive value from cloud-based analytic platforms, here’s what you need to get started:

1. Set some data standards. In the road to actionable insights, if your analytics platform is your engine, then data is its fuel. After all, predictive models will only function as well as the data you feed into them. Make sure your input is as clean and well put-together as possible. After all, it’s gargage in, garbage out.

Check that your enterprise or marketing data warehouses can feed data into your analytics platform in real-time. The goal is to drive 360-degree connectivity across all consumer touchpoints. Make sure to connect only those data-sets that drive insights and decision that impact the customer experience, not every byte of your warehouse. Certain data stores that are not mission critical and those that do not directly influence your marketing decisions does not have to be fed real-time or linked to your analytical engine.

2. Measure what matters. Just because you can measure and report on something doesn’t mean you need to build a KPI to track it. Be specific and frugal with the numbers you report and track, focusing only on the core metrics that drive your business. Ask yourself whether a certain metric will help your team make better marketing decisions.

Remember that the more metrics you squeeze into your dashboard, the less likely that the user will focus on the core KPIs. Keep it simply by just measuring and managing what matters. Do not built a dashboard with every metric conceivable, it only ends up confusing your audience.

3. Make decisions faster. Making faster decisions does not imply making hasty decisions, but most marketers need to shorten their test-and-learn cycles. Build a set of business rules that can action based on core KPIs: for example, if metrix X reaches level Y, we should shift Z% of marketing dollars to fund program Q. Most managers don’t make bad decisions with good data – they make bad decisions with bad or missing data. As long as your analytical engine can deliver good data and insights, expect your team’s decisions to get better over time as well.

Good managers and executives are adept at looking at KPIs and deciding how to evolve marketing strategy based on insights. However, while they do this innately, its important to empower your team and partners to make bold decisions based on the data. It’s about being agile and applying insights from cloud-based platforms to drive future decisions.

In an era of disruptive technology, it’s not the big that will eat the small, but the fast that will eat the slow. Leverage the cloud to personalize, optimize, and predict the best way to interact with and market to your consumers.

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