Head in the Cloud

Yesterday at the Pervasive Software Metamorphosis event I spoke on a panel hosted by the esteemed Ray Wang and on this panel, which was for an audience of journalists and analysts, we talked about the cloud and big data.

Here’s my take on a range of topics we discussed:

1) Amazon Out(r)age

It happened and we should all learn from it. If you have revenue flowing apps – transactional – running over Amazon and didn’t have redundancy built in you were in serious trouble and still are. For companies that can afford it this means a backup cloud with replicated data but for others it means paying more money to Amazon in order to spread your risk across multiple regional datacenters and many availability zones.

If you don’t have a transactional application you still have to have a strategy for how to deal with an infrastructure failure but it’s potentially less fatal than those apps which flow revenue. Basically you have a little more breathing room.

This isn’t about cloud vs. no cloud and the reason why you have not read about a backlash fueled by the old guard is that everyone has skin in the cloud game now. Why would any company market against their own strategic initiatives even if it means scoring points against Amazon?

2) Database Architecture

There was a brief conversation about big data as it relates to database architecture, as in relational vs. non-relational (e.g. Hadoop). This is an important debate but it’s still the wrong one… whatever the database architecture is that you commit to, you still need database architects to design and then manage the database interactions.

It also seems like we are missing the bigger picture, which is what is post disk drive. In my mind the more interesting trend is the move to entirely in memory architectures for data management. This is important not just because of the significant performance benefits they deliver, not to mention power management and thermal load, but reliability.

On performance alone this approach more than justifies the shift because not only does it make what you already do faster but the performance creates new business application opportunities as a result of what becomes possible, such as pattern recognition on very very large datasets. I predict that within this decade we will see a wholesale movement toward in memory architectures for network storage and disk drives will predominately serve archival and backup needs.

3) Big Data

This is, in my mind, the most exciting trend of the last decade. We generate so much more data than was ever imagined and I am quite sure that in years forward we will continue to say this even in light of what we are already seeing. The web is shifting from pages to streams and these streams are incredibly expansive as each iteration adds more content and even more metadata.

Think about all the stuff that is attached to something as compact as a tweet… time/data, location, profile, bits for favorited, promoted, retweeted, searched, and much more. I don’t profess to be an expert on Twitter’s data model but it’s a great example to demonstrate how a very small piece of unstructured text can balloon up into a much bigger data object.

We are also becoming adept at dealing with media types in our online interactions and because we suffer no penalty for data storage usage we save everything. We have cameras that make sharing of 8 megapixel images and very large video files effortless. These images and videos are then propagated through the many social networks that we participate in.

Business applications are not immune to this either, for the same reasons. Storage is cheap, relatively speaking, and processing performance means an app can access and manipulate large amounts of data. Gone are the days when compactness and efficiency were required not just for neatness but the economics of applications on expensive hardware devices. Today we capture everything even if we don’t know what we will do with that data.

The good news is that cloud integration capabilities, Webhooks, and sophisticated API data pumping stations mean that all this data can be exploited for purposes other than what it was originally captured for. New applications will develop as a result of the ability to easily hook into these large public data sources.

Cloud integration of data is a necessary topic to discuss because just because you can get data doesn’t mean that you have the right to use it. Data ownership and regulatory driven privacy issues are a major concern, the lack of a unifying standard is admittedly an obstacle. Datamarts will evolve as a result of these issues, serving as a broker or syndicator of data streams.


The Interest Graph, People are Complicated

For several years now we have become comfortable with the computer science notion that a graph maps our people connections. The concept of social graph has moved from arcane geek speek to that of mainstream concept, thanks largely to Facebook but certainly not exclusively because of Facebook.

In the U.S. alone more people have social network profiles than don’t and this entry point to building one’s own as well as being a member of the social graphs of others has popularized the notion while revealing the incredible opportunity that exists for companies to explore and exploit the relationships people maintain. It’s a way to discover and extend our own knowledge and sense of connectedness.

The interest graph is not all that different from the social graph, instead of mapping our connections to people the interest graph maps our relationship, and ideally the intensity of, to the things we identify through our online behaviors as having an interest in.

What we are all learning is that at any given point in time we exist on the Internet at the intersection of content, social behaviors, and social networks. This is in itself a pretty big shift from what the Internet was originally conceived to do but is also true to the vision that technology can connect people and things.

Social graphs have many dimensions and the fact that social networks have enabled these graphs in a flattened state reveals the single largest shortcoming that impedes innovation on the social graph. People are complicated, we exist in many social planes whether it be personal friends, professional relationships, schools, family, activities, location… the list goes on.

Interest graphs are also multidimensional but in a way that is perhaps more convoluted. Yes we clearly express interest in topics but we also express interests in brands, celebrity, time based events, have a language orientation, and like the social graph, an interest graph has many planes defined by, not ironically, the social graph that is being lensed through.

The concept of interest graph is not new, companies like Pandora and Last.fm are based on the concept, Amazon brilliantly unleashed this on shoppers, and more recent companies like Quora are very much tied to the notion of content and people discovery based on expressed and inferred interests. What is different right now is the sense of readiness that brand companies are exhibiting; there is a clear appreciation for the untapped potential that social and interest graphs contain and a willingness to innovate.

If you are a brand company why should you care about a person’s interest graph? Most immediately it provides you with a window into the things that an individual person cares about, which then leads to the opportunity to target promotion and advertising in an intelligent way that not only improves the response rate for promotions but also reinforces the connectedness of people to brands.

If the interest graph begins and ends with better advertising and promotion, it will be a massive disappointment. The potential to drive brand advocacy as a result of interests and affiliations with other brands is so large that it borders on the incalculable. People associate, by choice, themselves with many brands in their day to day lives, and not surprisingly there is a strong overlap of constituencies based on the personality of the brand in question.

It’s too easy to say Ford, NASCAR, Budweiser and Walmart… but it is an effective illustration. Perhaps more subtle is the relationship that a company like Apple has to other brands, Nike being a good example. From a demographic standpoint there is a clear connection but also at a product level with Nike embracing Apple’s iPod technology. The point is that brands don’t exist in isolation, they exist in our consciousness in relation to other brands that we identify with.

The interest graph unlocks these relationships in a machine format and enables not just promotion but also content discovery that reinforces those relationships. The ability to introduce new products by targeting not just a company’s most passionate followers but also those of brands that are strongly associated with a company is a disruptive capability.

Lastly, the ability to mine the collective interest graphs for a company’s followers – those people who have opted into a brand – reveals a deep level of insight into the hierarchy of needs that the collective ascribes to. Starbucks did some fascinating work with Research.ly that brought this to life.

The interest graph is defined by connections, but it is brought to life through self-expression. When we combine brand-centric relationships and conversations, the interest graph eventually evolves into what is essentially a brand graph. Within each brand-related graph is a group of highly connected individuals that serve as a company’s network of influence. The ReSearch.ly team extracted 50,000 of the most recent Tweets that included a mention of Starbucks. We then analyzed the connections between people and identified the top 100 individuals and the number of their followers who also mention Starbucks within the 50,000 mentions. We can then bring to light Starbucks influencers as a representation of its brand graph and influential hubs. As we can see, the difference between monitoring and gathering intelligence allows Starbucks to now identify relevant networks and introduce personalized campaigns to further spur advocacy and loyalty.

Social CRM at the Crossroads

The last 2 years have been banner years for social CRM technology where the term itself went from being derided as being made up by vendors and analysts rather than defining an actual technology segment, to one of enthusiasm and excitement for how social technologies are changing the way companies engage their customers.

Interesting as that is to observe, many questions still linger about whether this is in fact a product category or a catch-all category to describe a collection of product categories that are probably too small to exist independently and matter, or more to the point, these subcategories are deployed collectively to enable a social CRM strategy. Gartner Group doesn’t even acknowledge that social CRM is a product yet they have a Magic Quadrant devoted to it as a product category… explain that schism?

For what it’s worth, I fall in the “who gives a shit category”… we make up descriptors all the time to explain marketplace trends that defy historical categorizations and reflect broader macro trends that disrupt the status quo. Social CRM exists largely within this context, it is a “I’ll know it when I see it” category.

Take a look at the CRM Idol competition that Paul Greenberg and a raft of influential analysts, journalists, and pundits are promoting. First off, it’s not “Social CRM Idol” but rather “CRM Idol” and social CRM is but a subcategory of qualification. In fact, in this context I’m not even sure what social CRM is other than a label for vendors to opt themselves into, because if you look at what a social CRM vendor would encompass it would all be represented in the other categories.

  1. Traditional CRM Suites
  2. Social CRM
  3. Sales – Sales Force Automation, Sales Optimization, Sales Effectiveness
  4. Marketing – Marketing Automation, Revenue Performance Management, Social Marketing, Email Marketing, Enterprise Marketing Management, Database Marketing
  5. Customer Service – all permutations
  6. Mobile CRM
  7. Customer Experience Management
  8. Social Media Monitoring – requires the possibility of integrating with a CRM technology
  9. Customer Analytics – including text/sentiment analytics; voice based analytics; social media analytics, influencer scoring, etc.
  10. Enterprise Feedback Management
  11. Innovation Management
  12. Community Platforms
  13. Enterprise 2.0 – collaboration, activity streams etc.
  14. Social Business
  15. Knowledge Management – this one requires the possibility of integrating with CRM systems
  16. Vendor Relationship Management
  17. Partner Relationship Management

Traditional CRM has existed to date in the oak paneled cigar smoke filled back room that is enterprise software, it is expensive software built for use by employees. The fact that it is developed for employees is not a criticism, just an observation, but that focus forces architectural issues that then becomes the culture of the app itself which presents enormous obstacles for repurposing to consumer usage.

Nothing about CRM software cries out consumer use, and that doesn’t stop with the user experience but also the pricing and support model. It requires authentication and is architecturally challenged when it comes to lightweight user modes like someone logging in from their Facebook account, plus it is priced by the seat, which by itself rules out consumer usage.

The evolution of business is all about the reduction of latency and disintermediation through technology, as in the elimination of human action. We went from calling businesses during business hours, or visiting a location, to extended and 24/7 call centers and then email and then the web. We have reached a point of disintermediation where we no longer even want to go to them, we expect that a tweet will be responded to substantively in a matter of minutes. This is the world that customer facing organizations now live in.

As a consumer I also have an expectation that I am a power of one, even when backed up by my extensive social graph. I really don’t want to be treated as part of a group and even for the most ordinary of products I want companies to treat me as a human being that is individual and distinct from every other customer that company has.

This is perhaps the most significant challenge that traditional CRM approaches have to overcome in a consumer environment, they simply are not very good at translating the reams of unstructured information that is a result of consumer engagement into structured CRM content. As a result, CRM systems have a reflexive need to categorize and group customers based on demographics, which while useful does not address the dynamic of how I behave as a customer.

The intersection of social and consumer is precisely where social CRM exists, not CRM as we have understood the product category to date. But this isn’t to suggest that social CRM displaces traditional CRM, in fact the opposite is very much the case. As CRM suites embrace social and consumer behaviors through community platforms, social media engagement, game dynamics, and location based services they reveal a life of the customer that becomes incredibly valuable in the context of a CRM backoffice suite.

However, this is not to suggest that CRM suites become the de facto social CRM enabler because from a product architecture and business model standpoint these products are very challenged in the social environment that consumers live in. They demo great but in terms of mass market adoption across SMB and enterprise businesses there isn’t much to point to.

Last week I made a comment in a broader conversation about Get Satisfaction being a social CRM offering and my friend, who is a respected analyst in the space, called me out on it by asking if we define ourselves as social CRM. My response to him was that yes sometimes we do but it depends on the perspective of the person I am talking to.

Social CRM segments exist in the context of what lens you are looking through, whether it be sales, marketing, or customer support. In each case what you would define as the baseline social CRM functionality will be different but the overriding concern is that customer engagement is a new and powerful form of marketing so it is not about one functional perspective being more important than another. This is the dilemma of social CRM.

Many commenters have pointed out that the many sectors of social CRM are going through or will enter a period of consolidation. I agree and disagree… there will be more M&A as customers increasingly put in place more sophisticated social strategies that require more pieces and companies will respond will rolled up suite offerings. However, the pace of innovation is increasing so rather than consolidation shrinking the vendor landscape, this will have the effect of increasing the number of companies operating in the space.

Social CRM is targeting a market opportunity much bigger than ECM (and collaboration) and CRM combined, which is rounds up to $25b a year. Social business technologies have the capacity to reshape how companies goto and engage their markets, and the applications themselves will cross business boundaries defined by operational responsibilities in a way that ECM and CRM alone would not.

Blame the Ratings Agencies Redux

The irony about the S&P downgrade on the outlook for U.S. Treasuries from “stable” to “negative” is that the White House downplayed this as no big deal and ultimately a political commentary, yet just last year the President enthusiastically signed into law the Dodd-Frank financial reform bill, which among it’s many (many) provisions included language that sought to regulate ratings agencies by making them subject to legal action for misleading forecasts and ratings.

The rationale that Dodd-Frank provided is that ratings agencies had to be held to high standards through the threat of legal action that would subject them to punitive financial consequences for failing to apply thorough review processes as a backbone to their ratings products… so the question that should be asked of this Administration what is it, are the ratings agencies wildly speculative in spite of the consequences spelled out in Dodd-Frank or do they have a point? While it could be argued that the S&P action is a little late considering the world’s largest bond fund dumped their entire position in U.S. Treasuries 5 weeks ago.

The fact remains that elected officials love to complain that ratings agencies are in bed with corporate interests when it comes to ratings and therefore have a flawed system for analysis… yet when the tables are turned and these same agencies are critical of government backed bonds then the agencies are, according to these same elected officials, being unreasonably stringent in their application of analysis and methodology.

CalPers, which is at it’s core just another form of government entity for all practical purposes, sued a range of bond rating agencies in 2009, and then in the very same year CA Treasurer Bill Lockyer climbs up on the soap box to decry the poor ratings that agencies were giving CA bonds, complaining that poor ratings were costing the state untold millions in additional interest payments. Hypocrites… all of them.

Selling My Personalized Rate Card and Amazon’s New Kindle Pricing

Amazon announced a version of the Kindle that can be had for $25 less, providing you are willing to subject yourself to screensavers that are ads and banner ads at the bottom of the home screen. I don’t have a problem with ads but my reaction is still negative.

Amazon is saying I am only worth $25.

Okay so Amazon has to create the market first but with their volumes they won’t have a problem doing that. However,  I know I am worth a hell of a lot more than $25 given my demographics and purchasing behaviors, a fact Amazon knows very well given my transaction history, yet Amazon is flat lining me and making, potentially, a lot more on the arbitrage of the discount they are giving me relative to the ads they can deliver to me assuming I bought the device.

Interestingly I really don’t have a reaction to the ad-powered Kindle but I do have a negative reaction to Amazon on the grounds of basic fairness. I should have more control over how much I can sell my ad attention for and Amazon should deliver this in the form of dynamic pricing that gives me a bigger discount on a Kindle.