It is in this climate that affiliate marketing people look around and start to wonder what has been going on in the market — a whole new class of service providers have emerged on the basis of a technology that the affiliate networks owned for more than a decade.

Retargeting is the keyword, and there are quite a few fast-growing companies (some with more than 100 employees already) that are pushing hard on their internationalization. And guess what? Many of them officially price on CPA.

Now is that a threat or an opportunity? They have their own tracking and get their pixels much deeper in the shops on the advertisers’ pages. Moreover, they start to recruit publishers and build own networks by offering decent CPMs. Their reach is based upon smart remnant inventory buying from large portals, ad exchanges, and/or ad networks. On a first impression, this appears to be not quite the reach that affiliate networks have been able to monetize with regards to their eCPMs. On a second view one could say that affiliates have been reaching out to that type of inventory already via post-view commissioning, programs with 100% confirmation rate and some other tweaks that allow for proper publisher risk-handling in that little arbitrage universe.

Retargeting seems to be an additional way to generate sufficient eCPMs in order to buy reach from the “brand sellers,” and affiliate networks start to come up with ways (like enhanced container tracking) to integrate that business into their networks. Ideally those retargeting players would become an additional powerful publisher segment in their portfolio. The value proposition of the affiliate networks is strong as they can wave the banners of hundreds of potential advertisers (though not every advertiser works in that model).

The downside is that retargeters (alternatively called “remarketers”) did a good job in selling their services to advertisers directly. Moreover, they managed to sell unlimited campaigns on less risky and more profitable models (CPC and post-view CPA). And the advertisers are happy with the CPC model, as they see the retargeters reinvest their profits much faster in additional reach on the basis of a strengthened cash flow.  So the question is: will retargeters start to move into a kind of symbiosis with affiliate networks for the sake of fast advertiser growth, or will they dare to continue to place their own tracking tags, grow their own sales forces, and maintain their pricing levels in a direct customer relationship?

This will be interesting to follow…

Online newspapers struggle to stay affloat

Yesterday The Guardian reported that The Times, which moved to a full-scale paywall system last month, “lost almost 90% of its online readership compared to February since making registration mandatory in June.” Though The Times is making new revenue from the folks who’ve opted to subscribe, that’s still a pretty hefty hit (or rather, loss of hits) for one of the world’s premier newspapers. With such a dive in daily readership, it seems unlikely that The Times would be able to continue charging advertisers the same prices for their ad inventory when these advertisers could easily shift to un-walled sites that can offer more impressions.

In a world where most consumers, especially the so-called digital natives, have been trained to expect free content from even the highest tier publishers, how can newspapers continue to offer their high-value content for free (or at least for prices the public will agree to pay)?

As with print newspapers, the costs that are not covered by online subscriptions are to be made up by (digital) advertising revenues.  But Advertising Age reports that, though newspapers still fetch higher prices for ad space than other online publishers, their share of the web’s overall digital advertising spending is shrinking year after year — and this in spite of the fact that overall spending on digital advertising continues to rise.

So what can newspapers do to help increase ad revenues and compete with the aggregation websites and “content farms” that are threaten to win their audiences?

There are many ways that newspapers are attempting to up the ante to compete with these kinds of sites, sometimes including partnering with them for local news coverage. But are newspapers exercising the right muscles when it comes to getting the right prices for their ad inventory? (FYI: In the ad industry both on- and offline, the price of an ad space is calculated in CPMs, or cost per thousand impressions.) The article from AdAge (linked above) suggests that that competing news sites are winning advertisers by taking advantage of the newest digital ad technologies.

“Advertisers are warming to competing news sites because they’re finding a better combination of scale and ad technologies like targeting,” warns Advertising Age. “When Michael Hayes, a former newspaper pro who’s now a digital-media buyer as executive VP and managing director at Initiative, wants to target an auto dealer group’s ads to local consumers actively shopping for cars, he usually goes to big, technologically advanced players.”

To stay in the game, it seems that in addition to exploring new ways of reporting and distributing news, newspapers will need to step up to the digital advertising plate and begin to match their opponents’ interest in cutting-edge digital marketing technologies. With companies like sociomantic offering the possibility to deliver the most relevant ads to best-matched potential buyers, newspapers and other online publishers can benefit from the higher CPMs they can charge for offering a higher-quality audience, and advertisers can benefit from reaching audience members are are more likely to convert.

Which side of the audience line do you fall on?

Are you willing to pay a subscription fee to access high-quality content, or would you rather that online newspapers start showing you ads that are more specifically tailored to your lifestyle and interests? It may take a combination of the two to save the players in this struggling industry, but only time will tell.

Once per year, more than twenty representatives from the Interactive Advertising Bureau gather from all over Europe to share their views on general market development – quite a sound reason for 300+ players from all parts of the digital marketing industry to jump on a plane to this networking opportunity. And of course it doesn’t hurt that this year’s Interact took place in sunny Barcelona. The stage was set in the beautiful Casa Llotja de Mar, the corporate headquarters of the Official Chamber of Commerce of Barcelona.

La Casa Llotja de Mar | photo by Press Cambrabcn on Flickr

What could be clearly identified as the hot topic on everyone’s mind was the big worry about how to maintain high gross profits and growth in the online branding world amidst the “threats” of direct-response-addicted advertisers and game-changing volumes of social media traffic. The question tickling everyone’s brains: how to sell branding when advertisers have been told for years to watch their CTRs (and increasingly tougher online marketing metrics, like CPA)?

Randall Rothenberg (President, IAB U.S.) described this backfire best by speaking of the “tyranny of the click.” Media agencies, sales houses, and inventory owners seem to go round in circles talking about new KPIs and technologies to better their value proposition; meanwhile, advertisers develop a life of their own, bypassing the existing structures.  Not for nothing did Patrick Rona (President, European Operations Tribal DBB) preach caution when pointing to Unilever, who took their board to the Valley looking for new ways to reach out to customers.

Most impressive was Jef Vandercuys (Digital Marketing Head, Anheuser-Busch InBev), who managed to become one of the biggest global budget owners leaving TV with a pitiful 20% of the Anheuser-Busch marketing budget for this year — an enormous plunge from the 70% they spent on TV  in the previous year. You could feel that this guy was already far ahead of most of the people in the room: focusing on customer dialogue in social media, managing conversations via individual high-tech dashboards. His interest in social media was not because he was impressed by the massive traffic in that area, but because of his understanding that he reaches his target group at that exact point of time when they decide on their favorite brand of beer for the rest of their lives. For Vandercuys, large-scale branding campaigns increasingly become the trigger for the Anheuser-Busch social media activities.

This attitude goes hand-in-hand with the absolute shocker presentation of the conference: Darin Brown (President Global Accounts and Innovation, Razorfish) dared to look two steps ahead by proclaiming that the concept of campaigning is going to become increasingly outdated. Apart from individual marketing success stories (e.g., Marmite and Evian, see below), he sees a strategic shift toward customer-centric marketing strategies  in which continuous, bilateral advertiser streams of content and information (called “brand narratives”) play the central role that has previously been played by individual campaigns.

So following that idea, who will be the future money makers in digital marketing? According to Brown, it’s going to be creative content providers and technology companies that provide services in the field of conversation analytics.

You could see the branding guys who paid close attention leaving with dropped jaws, having realized – after Jef and Darin’s decks – that time is not on their side.

Last November, Libai and co-authors Eitan Muller and Renana Peres published “The Social Value of Word-of-Mouth Programs: Acceleration versus Acquisition.” As a company that uses social network analysis to provide businesses with intelligence about their customer influencers and other aspects of their customer networks, we found the implications of this research fascinating, so we wanted to give a brief overview of the research findings and what they imply for the application of customer network analysis.

WOM FTW? (or, ” Word of Mouth For the Win?”)

Word of mouth initiatives have long been a staple of the marketing diet, and in recent years so-called “influencer” targeting has become the go-to extension for the traditional WOM marketing models. Whether they’re labels as influentials, opinion leaders, or hubs, finding these influencers in a vast and complex network of customers is no small task; in light of the costs, managers often struggle to “achieve financial justification,” for this sort of marketing, though many are convinced of its benefits.

Prior to this paper, most of the research measuring the “social value” of influencers used soft metrics like message diffusion, conversation, or brand awareness; the monetary effects of WOM contagion have not been thoroughly defined in research. Libai and his partners are some of the first to attempt to answer the big question of ROI, to define the social value created by WOM in terms of customer equity. They define the impact of these WOM seeding programs based on the interaction of two factors: customer acquisition and customer acceleration (defined below).

Defining the Social Value of a Customer

In order to get the most accurate assessment of a customer’s potential WOM impact, the researchers define an individual’s “social value” based on the absence principle presented in the famous film “It’s a Wonderful Life”:

For those who might not have seen it, this classic story shows the effect on a town if one particular man had never been born (e.g., his wife is a never-married old maid). Libai et al. suggest that measuring a customer’s social value requires a similar method: measure the change in value over the entire customer network if this particular node were removed. To determine that impact, the researchers used “agent based models” (think Sims 3 for scientists) based on real-life social network structures.

So basically, based on this method, if Coca Cola’s marketing guy wants to determine how much social value I have within Coca Cola’s customer network, he’d make an “agent based model” of their customer network, then run a simulated WOM seeding program on the model, first WITH me in the network and then again WITHOUT me in the network. Then he’d determine the difference in how much money they’d make (for a given period of time) in each situation – that difference is my social value. It answers the question: how much are my connections worth to Coca Cola over the course of my time as a soda drinker?

If it isn’t already clear, this method of defining a customer’s social value has huge implications for companies trying to determine the value of their their WOM programs as well as social media marketing programs: finally, a method to determine which nodes (ahem, FOLKS) in their networks can have the biggest impact on their profitability, and just how big that impact can be.

Acquiring new customers, Accelerating adoption from would-be customers

There are two major ways that WOM campaigns can affect a product’s market share: acquisition and acceleration. Acquisition is how many new customers decide to adopt a product who would have otherwise adopted another brand or not adopted such a product at all without the WOM program. In the business world, time = money, so the sooner you a customer adopts your brand, the more time they have to spend money on your products – that’s the “acceleration” aspect. Acceleration is how much sooner people adopt a product due to the WOM program. Why does this matter? Adopting a product sooner gives a customer a higher lifetime value, so the sooner they adopt, the better! (For example, if I start buying Apple products at age 18, I am probably worth more to the company in the long run than if I start buying Apple for the first time at age 45).
The potential social value of a WOM program can then be determined in a similar manner — by comparing the “lifetime value” of the entire customer network with the program to the “lifetime value” of the network without the program (using agent-based models).

Sow your (marketing) seeds in fertile ground – but which ground is most fertile?

The WOM program type used in this study is what is commonly known as a seeding program, in which a company offers some sort of promotion (free product, discounts, service trials, etc.) to a “seed” group of people with the intention that these people will market for them via WOM. (Why? Previous studies have shown that customer loyalty is higher for customers acquired via “recommendation from a friend” than for those acquired via marketing).

One of the key questions surrounding seeding programs over the last decade has been whether or not it’s more effective for companies to seed via influencers or random people their customers networks. (This Fast Company article from 2008 gives a nice overview of the great influencer debate.) To investigate this question as well as the impact of competition on a program’s effectiveness, the researchers measured the (simulated) change in a brand’s customer equity in five different scenarios:

• no seeding program
• “random” seeding program without simultaneous competitor seeding program
• “random” seeding program with simultaneous competitor seeding program
• “influencer” seeding program without simultaneous competitor seeding program
• “influencer” seeding program with simultaneous competitor seeding program

The agent-based models were created based on 12 real-life social graphs from a variety of sources. The size of the seeding program (i.e., what percentage of the total network was chosen as “seeds” for a product) was determined based on industry standards, varying the size from 0.5% to 5% of the potential market. The “influencers” were defined as the top 10% of network with the most connections (highest “degree”), and the set percentage of “seeders” was chosen at random from this group. Conversely, for the “random seeding” program, the “seeders” were chosen at random from the entire network. Each of the five combinations of parameters listed above was run 20 times to combat the probability of an unlikely single run. These results were then averaged for each network to draw the final conclusions.

Research Results

At the end of it all, the research showed that the influencer seeding programs yielded higher customer equity gains in both the single brand and competitive scenarios, but  a competitive seeding program greatly reduced the overall effectiveness of a seeding campaign, whether the seeds were random or influential. Still, the results of the random programs were pretty good, so the decision about which program type to adopt depends on how much the company is willing to invest in discovering their influencers. Because it often requires complex, high-demand computing, customer network analysis can be time consuming and expensive, so some companies opt to let external vendors do their CNA –vendors like us.

One interesting point is that in a competitive scenario (e.g., when Pepsi and Coca Cola are both running simultaneous seeding programs), when the acquisition effect of the companies’ seeding programs is in essence “canceled” by the other program, BOTH companies can still benefit from the acceleration of their product in the market – getting customers sooner gives each of those customers a higher lifetime value, and therefore increases the lifetime value of the network overall.

The research offered in six other major results which we will summarize:

1. “The competitive program effect”: The social value of a seeding program is “considerably higher” when the firm faces a competitor than when they are the “sole player in the market.” This can be explained by the fact that in a market with no competition, everyone in the potential market will eventually adopt the available product/brand, so the gain is only from acceleration instead of a combination of acceleration and acquisition.
2. “The brand strength effect”: “Weaker” brands have more social value to gain from a WOM seeding program than “stronger” brands.
3. There is a threshold “seed size” for both influencer and random programs before the program actually decreases the social value of a company instead of increasing it. So more seeds does not necessarily equal a more effective program!
4. Influencer seeding programs reach that “threshold” much more quickly than random programs, so they reach their “peak” social value potential at a much smaller seed size.
5. While about 75% of a seeding program’s WOM potential can be achieved using a random seeder program, “targeting influentials can increase social value considerably” (p. 31).
6. The role of acceleration in increasing social value is more prominent in influencer seeding programs than in random seeding programs.

Why we care

One things that the research (self-admittedly) does not take into account is the cost of implementing these seeding programs. Each company would have to determine on a case-by-case basis what their social value gain would be less the costs of implementing that program, and “such calculations may demand network-specific analysis” for each company network and product.

Many companies have only just begun to realize the benefits of representing their customer networks for the purposes of customer network analysis. It’s a process that can be both complex and costly. For the companies who might not know where to begin this process, sociomantic labs may be a good place to start. We can take your existing customer names and put them into a network framework. And we can help you identify the influencers and analyze your network to determine the ideal WOM campaigns for your purpose, product, and people.

This fall, our front end customer network analysis SaaS will help companies help themselves to this sort of data and analysis. If you might interested in exploring for the closed beta of this service, please get in touch.

For a nice review, check out this presentation Libai gave at WOM UK conference in April:

The guys over at Altimeter put together this excellent report earlier this year in which they outline 18 use cases for sCRM. This is a great starting point to help businesses understand how they can use “social” means to reach their existing CRM ends. The use cases are broken up into six categories: marketing, sales, service and support, innovation, collaboration, and customer experience. (Wim Rampen suggests in this post that many of these use cases could — and should — already be in place within a traditional CRM framework. While this is true in part, I think even the “existing” cases certainly have much to gain by adding a social dimension, so it was helpful for Altimeter to include them in this list for the sake of thoroughness.)

As the Altimeter report points out in a quote from CRM “Godfather” Paul Greenberg, at its core sCRM is about moving from the transactional model (traditional CRM) to a new interactional model in which the “relationship” aspect of CRM is based on a conversation between company and customer. Businesses now have the opportunity not just to reach out to their customers, but to actually engage with them in their venue of choice, a process that offers huge potential benefits for both sides. For the company, implementing sCRM strategies can lead (at the most basic level) to better ROI and longer customer lifetime and loyalty statistics. The customer benefits from better, faster, and deeper customer service, support, product development, use experience, and maybe even more entertaining marketing . I think Jacob Morgan did a great job of summing this up on his blog:

The real value from SCRM comes from being able to change how your company does business and improving the user experience while building advocacy. Simply responding to as many comments or tweets as possible is senseless and not scalable.  A much better solution is to actually fix the problems the customers are identifying and collaborating with your customers to help give them what they want.  This is part of what being a social business is all about.

How It’s Done: Social Media Analytics VS. Social Network Analysis

There’s plenty of reading material about where and how companies can “begin the conversation,” and there is a healthy selection of social media monitoring/marketing tools. But, like Morgan, one of the key questions I’ve noticed with the social business sphere is the issue of scalability. Though these tools provide powerful social media analytics to discover information about the conversations (where they are happening, how often, by whom, etc.), as more customers adopt social means of communication, companies run the risk of missing some of the value in the midst of all the noise.  Social media analytics charts are a powerful and necessary element of a sound sCRM strategy, but they don’t tell the whole story. In a business world where 1:1 communication is growing simultaneously simpler and more challenging, how can companies discover whom to talk to, when, where, and how often – all while keeping the experience and product tailored to the customer’s needs?

One possible answer to this question can be found in social network analysis – or, in the case of companies, customer network analysis. Unlike social media analytics, which usually collects and analyzes the conversations defined by brand name or keywords, customer network analysis is an effort to make sense the of the chaotic web of relationships within an existing network of people – be they customers, prospects, or both. Though the concept of social network analysis has been around in sociology since the 1950s, only in recent decades have we garnered the computing technology needed to efficiently analyze networks with millions of nodes and edges with the swiftness needed to impact business results.

Customer network analysis (CNA) is therefore quite a different concept and practice than social media analytics. It’s a topic which, by my observation, has not yet made it into much of the sCRM conversation, and it seems that still some confusion about the differences. SocialCRMWorld has had some great posts highlighting a few of the implications of CNA for sCRM, but I’d like to sum them up here to highlight the differences between CNA and social media analytics.

CNA: Same game, different player

Social media analytics platforms tend to start with the brand name (or keyword) and work down through the layers of web conversation to discover the customers as they speak. This methodology can be used to answer questions about where web traffic is coming from, the effectiveness of brand messaging, campaign tracking, sentiment analysis, and online loyalty.

While these are all very important questions that definitely need to be answered, they leave something to be desired from the sCRM perspective. If sCRM is really about running a customer-centric business, isn’t it important to start with the customer instead of the brand? Customer network analysis starts from the other direction – we go from the names of your existing customers (or prospects) and work outward to discover a different set of answers about the customers and their network. These are a few of the sorts of questions CNA can answer:

• To whom are my customers connected (both within and beyond of my existing customer base)?
• Which persons are highly connected within that network?
• Which persons are highly influential within that network?
• Where are my customers on the web? (aggregated social profiles, preferred websites, etc.)
• What are the topical interests of my customers, on both an individual level and within clusters or groups of customers?
• How does information flow within and beyond my customer base?

When combined with existing CRM data (after all, sCRM is an expansion upon – not a replacement of—“classic” CRM), the answers to these questions can lead down many paths. Understanding precisely where your customers “hang out” on the web and how they use their preferred channels can increase media planning efficiency. Discovering your influencers and reaching out to engage with them can lead to faster product diffusion, collaborative product development, and increased word of mouth marketing. Incentivizing your “answer people” can help your best customers help each other. Strengthening inter-customer relationships can lead to higher loyalty and customer lifetime values. Understanding interest clusters and the opinion leaders within those clusters can teach you about new avenues in which to engage your customers.

Whether used for support, innovation & collaboration, marketing, knowledge management, or community development, it’s clear that there is an important role for customer network analysis in every mature sCRM strategy.

Not sure how to integrate CNA into your sCRM strategy? We’ve got a closed beta of our CNA solution coming this fall. Sound intriguing? Get in touch!

A few quick thoughts

I think this Animated Explanation does a great job of showing why cookies are a good thing, if you let them be. With so many (well-founded) web privacy concerns surfacing in the public consciousness this year, many people feel an immediate gag reflex to the idea that companies would want to collect any sort of data about them. In this climate, “cookie” in the web sense has become a bit of a dirty word.

But it’s easy to forget the good things that can come from this anonymous data collection. From user experience to product development, learning about the customer is an important part of what enables businesses to improve. At the end of the day, if the products and services that companies are providing aren’t improving, no one’s going to keep buying them. So the more information that companies can learn about an individual, the better they will be able to serve that individual.

In a world chock-full of advertisements, I’d much rather see ads for items or causes that are directly relevant and personally tailored to my interests — wouldn’t you?

Lars Kirchchoff's Facebook network rendered in Gephi

Okay, maybe not, but for practitioners and researchers alike, data visualization can reveal insights that aren’t always obvious from looking at the raw data, no matter how well organized it may be. When we’re talking about the sort of data we deal with here at sociomantic — social network data – visualization takes the form of a “social graph,” and it can be a powerful tool to discover deeper meanings and applications behind the relationships and communities within a network.

A few weeks ago we showed you some social graphs of the French political blogosphere created by our research partner Tim Highfield using an open-source network visualization software called Gephi. After exploring Tim’s amazing Flickr full of graphs and reading @kristtina’s recent introduction to Gephi, I wanted to try out some of these social graph visualizations myself.

The Alternatives

If you’re interested in something with less of a learning curve, there are lots of easy-to-use, mostly flash-based visualization apps for Facebook and Twitter. These are the ones I’m aware of:

Facebook:

• Social Graph
• TouchGraph Photos
• NameGenWeb
• Friend Wheel
• Friends Constellation

Twitter:

• Mention Map

The great thing about these apps is that they do most of the work for you. And a lot of them look pretty cool. The problem is that they don’t give you much room to explore. If you’re hoping to analyze your Facebook network with a little more depth — to discover community clusters and explore network science parameters like degree, betweenness, closeness, etc. –  I’d recommend using Netvizz and Gephi. Lars (our VP Product Development) told me about Netvizz a few weeks ago — it’s a Facebook app that allows you to make a .gdf file out of your Facebook friends or the groups you’re in (.gdf is the file type reader by programs like GUESS and Gephi).

Two quick notes about Netvizz:

1)      Right now it can only analyze the friends of your your Facebook “profile” (for individuals) and the members of groups you’re in. Hopefully soon it will be able to provide .gdfs for “Page” fans as well so brands and companies can do Facebook social graph analysis using Gephi, too.

2)      The .gdf files for the Facebook groups are limited to 500 randomly selected nodes, no matter the size of the group. (Theoretically you could generate the random list .gdf enough times to discover all the nodes in the group and combine them into one all-encompassing file if you were looking to do some serious network crunching.)

Here are some of the networks I analyzed using the .gdf from Netvizz in Gephi:

Analyzing a friend's Facebook network -- You can see distinct community clusters

Facebook Group "Graphs & Social Networks" : A highly connected network!

Here’s a quick key to understanding these graphs:

• Circle = Node = Facebook friend or group member
• Line = Edge = Facebook connection (friendship)
• Node size = Betweeness centrality (measure of how much a node connects otherwise disconnected communities)
• Node color = randomly chosen colors used to represent the communities/clusters, determined here based on their modularity class via the Louvain method

Taking a Closer Look at Using Gephi

I think the most interesting network I analyzed was Lars’ profile friends (see first image). You can easily see the different communities to which Lars is connected identified in the graph, and it’s interesting to see which nodes have the most impact over multiple groups.

Since I took screen shots along the way, I made this slideshow to explain the steps I took to reach the final visualization.

Since I’m still learning I initially followed the Gephi Quick Start guide.  They have a file you can use to try out this process if you don’t want to use your Netvizz .gdf.

From an industry standpoint, studying social graphs like these over time can enable companies and brands to understand things such as:

• Which individuals are connecting disparate communities within their customer base. (If Lars’ Facebook network was my customer base, I’d definitely want to make sure I am reaching out to our managing director Thomas Nicolai, who has many connections to multiple communities within the greater network.)
• Over time and using methodologies to determine parameters like reputation and bandwidth, you can discover which individuals are gaining influence within particular clusters (e.g., someone who starts small might become more influential over time)

This fall, sociomantic labs will be launching a web front-end solution which will, in part, help companies to be able to analyze their Facebook networks in a similar manner to the way that I have analyzed Lars’ network (but with less effort on the company side). What sorts of features would you be interested to see in a Facebook network analysis module?

(Please contact us if you might be interested in participating in our closed beta for this platform!)

Looks like there will be a lot of great presentations, but here are a few we’re especially excited about:
DAY 1

• Stream 1: Social Media and Online Branding
  “…Tom Smith of Global Web Index will share the latest findings and show how social media can positively impact branding. After a short presentation, he will be joined by Amy Kean, Head of IAB UK’s Social Media Council and members of that group who we will share case studies of the social media affect in action. This is an interactive session…”

DAY 2

• Keynote: Laurent Delaporte, Microsoft Advertising
  “Laurent Delaporte, Vice President, Microsoft Advertising EMEA will discuss how brands are putting online at the heart of their brand strategy – and how today more than ever you’ve got to crack online engagement to survive. He will share recent examples as well as the findings of primary research to show how brands can communicate online.”
• Panel: Opportunities and Challenges for Online Branding
  “The session kicks off with a 10 minute presentation from Steven van Belleghem of InSites Consulting with data and analysis on the power of online in terms of branding and advertising from a consumer perspective.”

Are you going to be at Interact? Be sure to tell us what you’re excited to see. And feel free to find us if you’ll be there, too!

Hope to see you there! More info to come!

Thomas, attentive and pensive on Day 2 (photo credit: Frenchweb)

Manish Metha, Dell
Intimacy and Scalabilty: Using Social Media To Manage Your Brand

• As a brand’s social media model grows, they often lose their ability to interact intimately with their customers. Metha suggests reconciling this negative relationship through “conversation clusters” — break down the conversations that are happening into distinct spheres of interest to better manage the interactions. Segmenting the conversations into different clusters will help provide more and better conversations.
• For B2B, social media should be about connecting “subject matter experts,” engaging the blogosphere, participating in the conversation

Emmanuel Vivier, Vanksen
6 Rules to Fail With Social Media

• “Marketing is like karma,” you have to give something if you want to get something.  You have to offer customers value to make your social media strategy work.
• He offered the following update to Forrester’s 2007 “POST” strategy for social media marketing:
  • Profile: understand the activities of your audience
  • Objectives: Decide what you want to accomplish
  • Strategies: What is the creative idea? message?
  • Tools: What tools, formats, platforms?
  • Evaluate: What metrics and KPI?
    • Our insight: We found “evaluation” to be a big thing missing from a lot of the social media talk at the conference. It’s clear that companies should be using social media to engage customers, but it wasn’t always clear what they could show the boss at the end of the day. This is where social network analysis and related analysis of customer lifetime value comes in.

Steve Knox, Tremor (Proctor & Gamble)
Perspectives on Innovative Word-of-Mouth Advertising — P&G Learnings and Future Outlook for Brand Markers

• Amplification of your brand without advocacy of your brand is a waste. (Don’t be caught with a “successful” viral marketing scheme that no one associates with your company.)
• A brief lesson in cognitive theory: To save brainpower, our minds operate in terms of “schema” — patterns that determine our expectations of a situation. Our attention can be grabbed when a schema is interrupted (things happen in an unexpected way) OR when two schema are combined in a “conceptual blend.” Brands must work to make their marking “mildly, not wildly, incongruous” with our existing schema if they want to get our attention.

Pauline Ores, IBM
Influence Starts @ Home

• As a B2B company, in order to influence, you must be influenced. Be knowledgeable, respond quickly, and don’t forget to react.
• The potential insights you gain by “listening” to your customers on the social web can only make an impact on your business if you turn around and feed that information inside, then grow upon it internally. At IBM, they use a highly successful internal social networking to drive innovation and improvement. No matter how big your company is, it’s essential for the internal communication to react rapidly to the external communication in order to see results.
• (Pauline, if you’re reading this — thanks for your insight and conversation! It was a pleasure to meet you and to hear about the interesting and innovative initiatives you’re helping to lead at IBM.)

Carlos Diaz, Blue Kiwi
Successfully Tie In Traditional Social Media Techniques Within Your Existing Multi-Channel Marketing Strategies

• You need to have an engagement strategy, not just a social media marketing strategy. How will you get your customers and potentials to interact with your brand in a meaningful way?
• Conversation from influencers is the most important for ROI. Find a way to filter out the “best” (most valuable) conversations and focus on these conversations.
  • Our insight: And how can you find those influencers and opinion leaders? With the guidance and insight of sociomantic labs’ social graph

Mike Butcher, TechCrunch Europe
Will the Next Wave Be Intention?

• In Web 2.0, marketing has gone in waves: social marketing > viral marketing > location-based. Is “intention based” the next wave?
  • Our insight: One of the main downfalls of existing social media monitoring systems is that they often provide conversation (complaints, feedback, wishes) to which companies can react, but they are seldom empowering brands to proactively pursue their customers and potentials. Because the sociomantic labs’ social graph is comprised of individualized information about the web life of the customer that goes far beyond their blog and twitter feeds — their life across the entirety of the web — we have the ability to provide a more comprehensive and telling picture to help companies predict the intentions of their customers on the web: where they’ll be going, to whom they’ll be listening, and who’ll be listening to them.

Barak Libai, Tel Aviv University
How Can We Assess the Real Value of Word-of-Mouth for Brands and Marketing

• “Social Value” is the monetary value a customer adds due to their social interactions. There are two dimensions in which to calculate this model. The first by the value of the product that the person buys because of a social interaction. The second, and far more complex, dimension has to do with the value of the people who are influenced to buy the product by this person.
• Determining customer lifetime value: In the social spectrum, we move from a measurement model of customer acquisition (now we have another customer because of marketing effort X) to a model of customer acceleration (we have another customer sooner because of marketing effort X)
• There is no simple way to calculate these values — there are issues such as of the number of friends influencing a single person (influence from multiple nodes), the amount of chatter surrounding any influential conversation, etc.
• Net Present Value (NPV) of cash streams: academics have learned that clusters of people (friends, people united by similar interests, etc.) tend to have similar lifetime values. So in order to determine how valuable any one customer may be, they could use what Libai called the “It’s a Wonderful Life” approach, in which they build a model to determine how customer lifetime value might be affected if a single person were removed from the bigger picture. This is the approach they’re taking now:
  • Collect data on real social networks
  • Run simulations on these model networks (think Sims 3)
  • Conduct experiments in these model networks (removing nodes — notice the difference between removing an influencer versus a non-influencer)
• What have they learned? Influencers are definitely important, but random seeding is good, too

Sumaya Kazi, YoProCo (formerly of Sun Microsystems)

• Big companies should think like startups when it comes to social media marketing. Startups benefit from having a united voice, and this is what big companies need. Startups have to use social media because they don’t have big budgets for marketing; big companies should take the frugal approach to social media marketing instead of waiting for big budgets to pass through the upper tiers.
• Great ideas from Sumaya:
  • Designed a Sun Microsystems Facebook group that promises “bytes” of info on a regular basis
  • “Sun Social U” training courses for Sun Microsystems to teach employees about Sun’s social media guidelines
  • Shared a conference they attended by distributing 100 (or so) Flip video cameras and having users upload their content in the form of one minute video interviews of people from the conference

The conference food was almost as good as the content (photo credit: Cyril Attias)

The big question at the end of the conference is how to harness the two-way-communication marketing trend. How can we make these all these conversations actionable? What do you think?

Below are some great resources folks have posted to document and comment on the conference. We’ll update this post as more materials become available:

Presentation by Michael Donnelly, Coca-Cola

Culture Buzz Video Aggregate

ESCP Europe’s recap video on Facebook

Hilarious video (“Send Us Your Reckons”) shared during the panel about the role of journalism in a Web 2.0 world