Category Archives: Analytics

The Marketing Technology Landscape

I’m not 100%  sure how to address the growing complexity of the marketing function, except to suggest that you take some time to re-evaluate and redefine what marketing is about. Consider layering in your technology mix along with your media and marketing mix. Then bring together a team of mobilists, technologists, data analysts and creative folks and you can get the ball rolling.

– Ted Morris, 4ScreensMedia

Algorithms Predict, Brands Build Relationships

Bloomberg news recently published “Can Computers Predict the Next Big Thing?” a perspective on predictive analytics. 

One of the most ingenious predictive capabilities involved the identification of ‘organic’ trends in the form of viral buzz.  By seeding the most talked about items, one brand’s campaign was successful in leveraging organic content  (earned media), resulting in a spike in sales.

At the end of the day, as the article rightly implies, the power of a brand lies in its ability to persuade and strike a chord at the emotional level in humans – the very thing an application or algorithm cannot do.

– Ted Morris, 4ScreensMedia

The Social Maze

Where are all my customers?

 The funny thing about all the endless advocacy of social media is that nothing has really changed in the business of matching consumers with brands. Oh sure, now that consumers ‘control the brand’, companies are at the mercy of infantile twittering tantrums such  as when consumers don’t get their way (especially on an airline) hoping to unleash a social firestorm primarily with the hope of getting noticed for a nanosecond or two. (The same folks likely get back on the same airline, content to collect their frequent flyer points.) 

One would think, with all those folks splaying their private lives out in public via the likes of YouTube, Facebook, Twitter, Flickr and Foursquare – lest we forget this thing called a phonebook or the science of geodemographics and credit card purchase data – that people would be easy to find. In fact, with all of the yottabytes of data out there about consumers, it should, in the year 2010, be a matter of running an algorithm or two to find customers, understand preferences and match any product or offer with any consumer 24/7 in any country with high Internet penetration.  It would be the end to the need to advertise using traditional channels.

Funny indeed. The search and storage/processing technology required to make the social web possible has, as the main output, data. Whether you call it media or content it’s still really just more data taking up space on some distant server farm deep in the Mariana Trench. As such, are we all the wiser? Not really. With free cloud apps having a shelf life not much longer that the vegetables in your local supermarket, many are wary of the risks of implementing something that will be obsolete by the time it gets traction in the marketplace. With the yet to be proven value of social media monitoring and analytics, it’s not as if the world has abandoned representative random sampling or in-market product trials.  

Do companies really have the strategies, skill sets or business processes to effectively leverage the social web? With only $2 billion slated for social media spending in the USA this year, I doubt it. Yet, evangelists are forever hopeful, as that is their stock in trade. Like Charles Revson, founder of Revlon once said, “In the factory we make cosmetics; in the store we sell hope.”  

On the other hand, Charles Revson didn’t have social networks at his disposal but his customers had no trouble finding the Revlon counter.  

– Ted Morris, 4ScreensMedia

Data: The New Capital of the Digital Age

Data: The New Green

The Economist recently ran a special report on managing information that prompted some thinking. First, some big numbers from the report: Wal-Mart handles over 1 million sales transactions per hour. Facebook houses some 40 billion photos (after only 4 years of operation). Cisco estimates that Internet traffic will reach 667 exabytes by 2013.

 With some 60 million people on Twitter, according to comScore data (November 2009), there are roughly 10 million tweets a day. This doesn’t account for the content – characters, photos, articles and video content. I also found that YouTube has generated more video content than all of the television networks combined have ever generated. The current upload rate is equivalent to about 100,000 Hollywood movies being made on a monthly basis. Finally, almost 100 trillion e-mails were sent in 2009.  

Bringing this a bit closer to home, consider the number of daily transactions that take place for banking, air travel, credit card processing, phone calls and e-commerce. You end up with some very large numbers indeed. This data also says a lot about how we behave. Most intriguing perhaps is what it can tell us, through the use of complex algorithms, how we might behave at some future point in time – and where new business opportunity may dwell.  

This growth in the information industry is not reflective of recessionary times. It points to a shift in investment, new business models, the laying of new infrastructure (servers, storage, cloud computing, software) and global workforce expansion in business information. It’s also transformational as the CIO’s role is increasingly one of contributing directly to business growth in contrast to the dogmatic notion of keeping the lights on in the boiler rooms of Enterprise Resource Planning and Supply Chain Management.  

It’s the effect of the peta, exa and yottabyte world that is most intriguing. Conventional ways to sense and understand consumer behaviour  will be challenged by the new wave of business analytics. Marketing research is but one example. If predictive analytics can do a better job of identifying which category of SKU’s is trending upward or which meal combo is gaining favour, what will marketing research be used for? Data analytics can also be used to generate new ideas for services, products and as importantly, help companies shed under-performing assets and balance inventories. By implication, there is a clear line of sight to the financial payback as firms like Amazon and Marriott have learned.  

This point from the Economist is worth noting:  

“…all these data are turning the social sciences upside down, he [Sinan Aral, NYU] explains. Researchers are now able to understand human behaviour at the population level rather than the individual level.”  

It’s no wonder Big Tech (IBM, Microsoft, Oracle, SAP etc.) is loading up on search, storage and processing capability. In exchange they will reap new profits from the digital age, largely unnoticed from behind the curtain of social networks and online store fronts.   

– Ted Morris, 4ScreensCRM  

Meet @Spam – Social Media Persona

This is @spam. Lots of followers, a ‘personal branding’ advocate and someone who is famous, at least, by some measure. You know, the type that likes to dispense advice, get your attention and loves to tell you about themselves in the most menial of ways.

Unlike the commercial “When E.F. Hutton speaks, people listen”…this is where is all ends, perhaps.

@spam. All about the ‘me’ in social media.

– Ted Morris, 4ScreensCRM