Sunday, July 28, 2013

BIG DATA vs SMART DATA: the next BIG shift of strategic marketing

Big Data is the biggest game-changing opportunity for marketing and sales since the Internet went mainstream almost 15 years ago.Big Data refers to any data sets which are so large and complex they are difficult to manage using traditional methods and software. This includes anything from medical records and military surveillance to the results of the Large Hadron Collider experiments. Today’s channel-surfing consumer is comfortable using an array of devices, tools, and technologies to fulfill a task Understanding that decision journey is critical to identifying battlegrounds to either win new customers or keep existing ones from defecting to competitors: therefore, organizations face overwhelming amounts of data, organizational complexity, rapidly changing customer behaviors, and increased competitive pressures. At the same time, the explosion in data and digital technologies has opened up an unprecedented array of insights into customer needs and behaviors. Those that use Big Data and analytics effectively show productivity rates and profitability that are 5 – 6 % higher than those of their peers. McKinsey analysis of more than 250 engagements over five years has revealed that companies that put data at the center of the marketing and sales decisions improve their marketing Return On Investment (MROI) by 15 – 20 %. That adds up to $150 – $200 billion of additional value based on global annual marketing spend of an estimated $1 trillion. Conversely, companies who miss big data opportunities of today will miss the next frontier of innovation, competition, and productivity. Analytics  & measurement have become more and more of a priority because every shareholder, CEO, and VP on the planet wants to make better decisions. Because of this, the business analytics market continues to innovate and grow at a solid rate big data can lead to better marketing through BIG testing: the key to better, more pragmatic marketing is actually the embrace of marketing experimentation as a driver of continuous innovation: new technology and new talent allow to start creating hypotheses. Then to use Big Testing to prove them out – right or wrong. The fundamentals of marketing remain the same, with the aims still being to build your brand, create awareness, and encourage trial, repeat purchase, preference and advocacy.So make sure your team has an excellent grounding in the old ways and an appetite to deliver them in new ways.

BIG data is now happening BIG time: What the ‘Big Data’ marketers are concerned with is mainly the digital content that’s being created at a phenomenal rate that you can use to gain insights into your customers.Think YouTube videos, social media platforms, Facebook Likes, Instagram photos, instant poll results, LinkedIn group discussions... It's even been called 'the sexiest new marketing tool around'.There’s now so much information available about customers that innovations are emerging to handle these disparate forms of data. It's imperative for marketers to understand these, in order to stay successful in the shifting digital landscape. It means that there are novel opportunities to deliver targeted customer experiences based on in-depth insights. This will enable businesses to develop relationships with customers and keep them engaged over the long term.Destination marketing is key when marketers start their Big Data projects by thinking of the end goal and then working through all the details. This so-called “destination thinking” helps the strategic marketer avoid the traps of many Big Data Marketing projects where the deliverable becomes the end goal itself instead of the business value imagined at the outset...
Although it’s mostly scientific , there is a specific art to approaching BIG data: leveraging actionable insight, customer segmentation is a good structure to start with , esp. when you merge attitudinal with behavioral: so if you apply the same sorting/logic of organization to social media, mobile or retail, you will keep a model that’s rich and can actually serve as a pillar of your marketing strategy & competitiveness...Example: collecting the likes on FB might be as rich in potential growth as the actual clicking on suggested links; understanding the questions that our customers are asking when they do a Google GOOG +0.07% search, visit a website or participate in a social media conversation... Start with the consumer decision journey : understanding that decision journey is critical to identifying battlegrounds to either win new customers or keep existing ones from defecting to competitors. Some 35 percent of B2B pre-purchase activities, for example, are digital, which means B2B companies need to invest in web sites that more effectively communicate the value of their products, SEO technology to make sure potential customers are finding them, and social media monitoring to spot new sales opportunities. One online retailer, for example, tailors its offers and discounts based on predictions of how likely a valued customer is to defect...
...and there also are some hurdles/risks to Big Data: obviously,  privacy is a primary one: with the recent outrage with the IRS scandal and big brother NSA revelations, American consumers might become more & more nervous about either Governmental or private entities mining & manipulating tons of personal information, even if it’s for straight commercial purpose: so give them clear/transparent information and let them decide how far they want to have their data utilized: most of them will not mind as long as they have been asked and feel in control of the level of privacy they set for themselves...That’s partly what Facebook had accomplished under pressure in the past 2 years...but failed to capitalize on after their collaboration with NSA was exposed during the scandal...

The field of applications in sales & marketing is huge: to start with , Retailors for whom it’s more strategic than any other industry because it’s reshaping their entire business & operating model: Walmart is using big data from 10 different websites to feed shopper and transaction data into an analytical system. Sears and Kmart are trying to improve the personalization of marketing campaigns, coupons, and offers with big data to compete better with Wal-Mart, Target, and Amazon. As the leader in the space, Amazon uses 1 million Hadoop clusters to support their affiliate network, risk management, machine learning, website updates, and more
More importantly, there is seamless commerce- also called  omni-channel- form of retailing, which lets consumers move seamlessly among all retail environments -- real and virtual -- as if they were one, will be the norm. For exampleH.H. Gregg and Jo-Ann Fabric and Craft Stores let their consumers check inventory by store, buy online and pick up the product at their chosen location. Restoration Hardware makes its stores into brand showrooms, where consumers can handle and test products while shopping the chain’s vast online catalogs and website. WalmartLabs is mining SoMoLo (social, mobile, local) data to predict shoppers’ next purchases and stock based on social-media activity.
It may seem like a simple task, but unifying the focus of a Fortune 500 retailer or manufacturer along these lines is a complex undertaking. First, you have to prioritize among hundreds of possible initiatives. Then you have to rethink the customer experience across channels and devices, and build the communications web to bring it together, from conference room to showroom. Within the organization, you need to break down functional silos and create incentives for different departments to share data and sell products from every channel.
Most retailers may have begun to adjust, with improved customer-service policies, new mobile features or updated product-delivery options, but they are still largely missing the mark. Still, several of the world’s most innovative chains are closing in on the ideal. Nordstrom’s, Best Buy, Macy’s, Urban Outfitter, Staples and Restoration Hardware are beginning to make the organizational transitions needed to develop a consistent experience for myriad types of shoppers.
Led by the belief that this is the future of retailing, these chains are uniting retail and e-commerce teams with one leader, integrating technology systems to act as one, seeking a unifying goal for the business (not the channel). Instead of year-over-year store comps, they’re measuring the combined impact of communications and sales across all channels. In stores, they’re adding quick pickup counters for online purchasers, training staff to handle instant checkout via smartphone and tablet and gathering data to personalize the shopping experience.

Consequently, this Big data  shift has interesting repercussions for the marketing consultants & partner agencies of advertisers: just as consumers can't be bothered with disconnected retail channels, retailers don’t want to juggle a dozen consultancies to accomplish something they’re too tied up to do in-house. They need partners capable of going from roadmap to results in a matter of months. So they’re starting to ask agencies to do things that Don Draper never imagined would be part of the scope of work. For starters, we have to help clients think through business policies, aspects of store layout and customer service. It doesn’t serve the business to cruise consumers through an elegant online experience -- picking out the products, finding the stores, checking inventory and making the purchase -- only to stick them at the back of a customer-service line when they enter the store for pickup. The hassle is amplified by the angst of people waiting to return faulty items. So we need to help wrangle with questions likes these: Do we have designated spaces in the parking lot for people who bought online to pick up in-store? Do we have a dedicated pickup counter? Are we engineered to make ordered items available for pickup in less than 20 minutes? Do we have cabinet space for all the products that are awaiting pickup?  Do we allow customers to return endless aisle products to a store location, even though they were purchased online? If so, how is that product returned to inventory? 

Other industries like Financial services are also leveraging Big Data for their product development: Morgan Stanley ran into issues doing portfolio analysis on traditional databases and now uses Hadoop to analyze investments “on a larger scale, with better results.” As well, Hadoop is being used in the industry for sentiment analysis, predictive analytics, and financial trades.

In Automotive, Ford’s modern hybrid Fusion model generates up to 25 GB of data per hour. Why? The data can be used to understand driving behaviors and reduce accidents, understand wear and tear to identify issues that lower maintenance costs, avoid collisions, and even confirm travelling arrangements.Insurance companies such as Progressive actually turn this kind of data into action to target various customer segments with appropriate, fine tuned  premiums & coverage solutions...

In the Entertainment industry, companies like Time Warner, Comcast, and Cablevision are using big data to track media consumption and engagement, advertising, and customer retention as well as operations and infrastructure. The video game industry is using big data for tracking during gameplay and after, predicting performance, and analyzing over 500GB of structured data and 4 TB of operational logs each day. Even brands like ESPN are looking to get in on the action.

The Hospitality or Travel industry have embraced big data for a few years , enabling them to go beyond the traditional analytics of customer loyalty metrics: British Airways is doing more to remember personal preferences with its “Know Me program” that can, for example, spot when passengers choose window seats for short-haul flights and aisle seats for long-haul flights because they want to stretch their legs, and that pattern can be repeated automatically. "They're combining everything they know about passengers, and historically that sort of information has been very fragmented across a variety of system," said Davenport. "They're also bringing that information to the front lines -- even to the cabin crews using iPads -- so it adds up to an impressive effort." Multiple airlines are pushing revenue management to the next level by calculating, for example, the value of a group of customers who will miss a connection due to a flight delay and then determining whether to delay their connecting flight or book them on the next plane.Travelocity applies analytics to pricing, inventory and advertising, and all three dimensions shift on a daily basis depending on supply and demand. It's using techniques like look-alike modeling, next-best-offer analysis and recommendation engines to push the right offers to customers that fit certain profiles.


All these examples show the multiple and deep repercussions  that the BIG data revolution is opening: companies that understand that next necessary stage of customer centricity transformation on the heels of the digital revolution will be able to yield invaluable insight,  innovation  and competitive advantage for years to come...This is BIG !