Predictive Analytics: The Path to Profitability in the Digital Age
Cross-posted on LinkedIn, December 16, 2015
Companies with foresight and wisdom are heading down the road of predictive analytics to make thousands of business decisions to drive revenue, market share, and profitability in near real time. Hardware has advanced in recent years to the point where it can process unimaginable amounts of information, especially in the field of predictive analytics. Fathom this: Google processes over 20 petabytes each day. “How much data is that?” you ask… TechTarget’s WhatIs site explains that a petabyte is “a measure of memory or storage capacity and is 2 to the power of 50 bytes or, in decimals, approximately a thousand terabytes.” Still not grasping it? The capacity of a human being’s functional memory is estimated to be 1.25 terabytes.
Translation: Machines can do things that weren’t even dreamed of twenty years ago. Not only has the capability of computers risen sharply, the costs of using them has become very affordable and with the advent of cloud computing there is almost no need for capital outlay. This means that massive processing power and predictive analytics solutions can be brought in to have profound impact on controlling sales revenue. This is done by aggregating databases and running predictive analytics over the top to precisely identify each and every revenue opportunity regardless of the number of products, markets and applications. So if you’re a company with multiple products and a slew of markets, this is your proverbial pathway to sustained profitability in the digital era in which we live and do business.
To substantiate the premise that companies need to look long and hard into upping their data analytics game, an article from the New York Times explained how Procter & Gamble, the world’s largest advertiser, made a major change to their advertising strategy. It had a lot to do with analytics. Journalist Sydney Ember writes, “‘The entire ecosystem of media and advertising is transforming,’ said Marc Pritchard, Procter & Gamble’s global brand officer. ‘We still want to get mass reach, but we also want to be able to do it with a greater degree of precision.’ That, he added, requires robust data and analytics and ‘better real-time planning and buying,’ with the overall goal of connecting with consumers with the right message at the right time.”
Read more here: Proctor & Gable Switch Advertisers
Modern Analytics has joined this crusade by launching the Model Factory which revolutionizes the production of predictive data models, a technology or process referred to as, “autonomous data modeling.” Old school predictive data modeling is one size fits all, cost at minimum $10k-$15k per model, is people and capital intensive, takes months of elapsed time, requires expensive software, and has issues with accuracy and being actionable in a real time world. It’s simply impossible to dwell in this paradigm if you want to generate thousands of automatically updated predictive models (which result in significant sales growth) and be able to stay tuned in and zeroed in on your various customers, products, and markets.
With the Model Factory this is not only possible, it’s right at your fingertips. Here’s a great, descriptive example to illustrate the huge opportunity upside…
Company type: Leading manufacturer
- 300+ product categories
- 5 predictive model classes created – best new prospective customer, existing customer cross sell and upsell, next best product, customer retention
- Predictive models created for all categories for all model types and applications – 1,500 total
1 month set-up, one week to run all models first time
- Average of 4 models across 75 categories met governance and criteria for deployment into sales and marketing automation systems (e.g. Salesforce.com)
As the core data is updated, all 1,500 predictions (identified revenue opportunities) are rebuilt from scratch with no wait time – they are all prebuilt. And across any of the 300 categories at any time a new opportunity surfaces that meets governance and deployment criteria it is automatically scored and integrated with automation systems. This leaves your data scientists or data experts to identify new categories, new data, new variables and new innovations. Moreover, it works at a clip that would be impossible to achieve without the machine learning and proprietary methodologies contained wholly within the Model Factory.
Although the Model Factory software would be very difficult to replicate (It took over twenty-five years to develop it.), it is by no means difficult to use, nor customize. One reason for its flexibility is that it’s an open system. This means that you’ll be able change anything; variables, statistical preferences or settings, refresh rates, etc.
The best part… I am pleased to tell you that we are launching this exact solution, Model Factory, in the cloud starting at $7,500 month for unlimited use with no capital outlay. Normally we charge a setup fee of $15k… If you reach out to Modern Analytics by the end of Q1, 2016, and use promo code “pathway”, we’ll waive that fee with a one-year subscription. Join us by delving into technology that was once not even science fiction, but now, it’s not only possible, it’s absolutely conceivable, plausible, and within your reach and budget.