Octavianworld

November 3: "Technology, Campaigns, and Civic Engagement" at Harvard's Kennedy School of Government

Jerry Mechling's invited me to present to his Leadership For A Networked World class (STM-480) on Monday at Harvard's Kennedy School of Government on Monday.  Here's the abstract for the session:

"As the election season draws to a close, some have noted that the campaigns, and in particular the Obama campaign, have assembled enormously powerful assets in the groups they have assembled and facilitated through their web operations. (It’s interesting to note that they haven’t used particularly exotic technology to do this, but rather have focused their efforts and resources on facilitating a ‘think global, act local’ approach to presidential politics that harkens back to the old ward system.)

As a leader in the public sector, one question this raises for you is how you too should move beyond “online, not in line” applications of information technology in government, toward applications that support higher “civic engagement” after the voting is over. Let’s define the objective: by “civic engagement”, we mean involvement in civic affairs by an informed polity, where “informed” means an awareness and understanding of individual issues and of the trade-offs among them, and where “involvement” means constructive evaluation and advocacy in ways that make the ultimate actions of government better and more fair. Assuming you aren’t a closet monarchist, fascist, anarchist, etc. and think this is a good idea, what should your agenda be?

One way to think about this is to have a simple framework for the mechanisms you need. What should you do to get good civic engagement? Elements might include:

• better tracking the “performance” of our economy and society along dimensions we value (for example: GDP, income distribution,graduation rates, greenhouse gas emissions)
• increasing the transparency of how rules and laws get made (see also this)
• improving government’s ability to work with and through citizens to get things done, as the Obama campaign has done with groups (see also this); a key focus may be finding ways the technology can support meaningful engagement in small blocks of time and effort, much as the campaign web has done.

The objective of this class will be to help you be aware of what's going on and begin to assemble your own agenda. Questions each of you may face will include:

• What’s worth tracking, collaborating on, mobilizing for?
• What small steps can "entice" people into deeper and more meaningful engagement?
• What’s already out there supporting this?
• How aligned are these resources with what I think needs to happen?
• How do I act—cooperate, compete, and how?
• How do I sustain these resources—what’s the “business model”?
• How do I promote and manage them?
• How do I “govern” them to make sure they aren’t mis-used?

Here's one of my favorites -- New Zealand's Police Act Wiki.  (Congratulations to Simon Heep, Michael Utton, William Ool, and Susan Hanks, for their leadership on reducing speed limits on South Island roads, and to other major contributors!)  Have any other examples you feel are instructive?  Please let me know.

The "Wikipedia Index": A Proposed Metric for Your Firm's SEO Effectiveness

Doing a little homework for our upcoming talk at the CMO Club Boston dinner, and I'm laying claim to coining a new SEO metric term: the "Wikipedia Index".

Check out "Nestle" on Google.  The firm gets the top result, and the Wikipedia entry doesn't turn up until the 8th spot.  1/8 = 0.0125.   Nice job optimizing a variety of news, UGC, and corporate subsites to keep the unwashed masses' spin on Nestle below the fold.

Now check out "Unilever" on Google.  Again, the firm gets the top result.  But the Wikipedia entry turns up in third place, for a 0.33 score on the "Wikipedia Index".  Unilever's SEO strategy has left it "vulnerable" to letting others define and describe it.  

An absolutely high "Wikipedia Index" score is arguably not good.  Taking it one step further, look at it on a relative basis:  if your "Wikipedia Index" is ~3x other major firms', you may want to have a chat with your SEO team.

Art Meets Science In Online Retailing

Online retailing performance is under intense scrutiny this fall (Amazon's guidance is already down for Q4). How will others fare?  One way to unpack performance is by how well firms generate attract, engage, and convert shoppers, especially as compared with competitors.  

Displayed below (minus labels for now) is a visualization that does this.  Each bubble represents a firm whose online revenues in 2007 ranked in the top 100 of all online retailers, according to Internet Retailer's "Top 500 Guide" (2008 edition).  The size of each bubble is a relative indication of the number of monthly unique visitors to that firm's online retailing sites.  The horizontal dimension measures the ratio of the number of monthly visits to the number of monthly unique visitors -- the higher the ratio, the greater the presumed "engagement" with that retailer. The vertical dimension represents Internet Retailer's estimate of the conversion rate (orders/visits, as IR calculates things) across each firm's online retail properties.  I plotted the horizontal and vertical dimensions on a log-log basis, to help you see individual points a bit better.  I'm sure you can guess the identity of at least one data point.

The picture is a powerful one, as it allows you to do two important things in one glance.  First, it allows you to see what the primary challenge is for any given firm, relative to its competitors -- is it to better attract, engage, or convert customers?  Second, it allows you to calculate the value of an improvement -- knowing a firm's average order size, if we expand or move its bubble, we can estimate the total revenue impact.  (I know it doesn't look like it here, because we're showing pure-web, store-dominant, and catalog-dominant retailers all at once, but engagement and conversion are in fact somewhat correlated as you'd expect.)

If you're into fractals, you can imagine clicking on a bubble and seeing all of a particular firm's marketing campaigns displayed this way, then clicking on an individual campaign bubble to see how well different customer segments have been attracted, engaged, and converted too.  More creative types can view the display as an abstract expressionist symbol that there's hope in marketing (as in politics) that Mars (left-brained analytics) and Venus (right-brained creativity) can co-exist peacefully.  Fellow MITX judges reading this will rightly accuse me of being "so derivative". Jackson Pollock fans will just roll their eyes and say, "been there, done that":

Inquiries very welcome from potential clients interested in the analysis and its implications.  There are many interesting and useful variants to it as well.  I'm planning to do it again with newer data soon, and maybe even work in time (with motion) as a fourth dimension.

(Postscript: Jim Sterne's related post in MediaPost's "Online Metrics Insider")

Social Media Talk at CMO Club of Boston Dinner November 11

My friend Perry Hewitt, who is the CMO at Crimson Hexagon, kindly asked me to join her in presenting a talk titled "From Communications to Conversations: Understanding, Managing, and Embracing UGC" at the CMO Club of Boston dinner on November 11, 2008.

Google's Incredible Reversing Falls: A Structural Take on The Ad Market

Google just announced its earnings, which beat analysts' estimates and have its price jumping again. This, amidst all the doom and gloom in the ad business. Why? I see this development at the confluence of three things happening in the ad market right now.

1) While budgets are tight;

2) what budgets exist will continue to flow to digital media because of
a) their inherently superior measurability and
b) their faster and more flexible ad unit development and deployment cycles;

3) among digital advertising channels, a search click is the closest to a purchase.

But there are limits to how far this can go that are defined by the typical structures of media plans. A while back I linked to a podcast of this terrific talk by Doug Weaver. It's worth a listen again in times like this.

Nonetheless, Google's achievement is a freak of nature. If they can pull it off again in Q4, look for the fawning to begin again. Me, I'll be looking for them to move meaningfully beyond paid search as their primary business model, and will be closely tracking developments like this.

Top Retailer Priority This Season: Optimizing Discounts/ Promotions

The New York Times yesterday chronicled the depth of retailers' woes this season. Same store sales are down 5-15%. A Wachovia analyst noted: "The lesson retailers have learned is that they need to get promotional fast to wake the customer up out of his or her trance." Quotes like these will no doubt weigh heavily on retailer psychology.

So, we're now in a game of No-Limit Promotion Poker. Discount too little, and you're stuck with inventory. Discount too much and you blow your profits. With things as uncertain as they are right now, it's not hype to say that the stakes go as high as survival. As they say, you've got to play the other guy's cards and not your own. The good news is that in the digital world, your customers' and competitors' tells are easier to spot.

For example, let's say you sell a line of TVs. Make one model in your line a guinea pig that you're willing to experiment with a few days ahead of your other models. Experiment with price/ promotion each day, and make sure the deal gets reflected in the shopping engines that will be so popular this season (get ready for a flood of "smart holiday shopping tips" in the press over then next few weeks, and deals like Walmart's $10 toy promotion). Obviously you'll plot daily orders vs. daily price, as well as daily price change. And, you should probably plot daily orders against relative price/ price change (your price v lowest price on a shopping engine for that model -- and don't forget to watch eBay).

Now here's where it gets interesting:

1)You could A-B test price changes at different levels -- what's the difference in orders when we cut 5% vs. 10%? Or, offer 5% with free shipping vs. 10%?

2)You could watch behavior in the purchase funnel -- when we change prices, how many hits to the product page do we get? How many shopping carts get opened but abandoned? In financial markets, there's data on how many buy and sell orders there are at different price levels. This pipeline data is the marketing analog to the "order book" in financial markets.

3)You could offer price alerts as a registration incentive ("registrants get a 24-hour head start on our general announcement of any price change"), allowing you to expand your list and further segment it on price sensitivity (IMHO email marketing effectiveness will be crucial this fall).

4)It's a bit late for those who don't have this capability, but firms who can do personalization via first-party cookies should be exploiting it to the hilt. If the same cookie hits a particular product page three times in two days but doesn't convert, maybe it's time to personalize a price cut for this "incipient buyer" to see if you can push him/her over the edge?

5)You could play with where you offer a deal (in a store vs. online). We're used to thinking of online as the place to get the best deal, but maybe feature store loss leaders online to drive foot traffic and cross-sell?

The silver lining in the current crisis is that working on a specific issue like this with a "war-room" mentality creates an opportunity to improve firm-wide collaboration. Make sure you have a finance/ merchant/ marketer task force in place for your experiments. Sharing updates/ lessons is critical. Set up an internal analytics blog if you haven't already, and report what you're learning every day in addition to pumping out the reports. Summarize / log the decisions you're making there too, so you can tie cause and effect clearly. Don't leave it to chance that your colleagues and bosses will see what you think they should see. The main thing right now as a firm is to be well-coordinated -- "If you can keep your head when all about you are losing theirs..."

There are many more ideas like these, and their applicability will depend of course on the particulars of your business. The main message is that the time is right for a highly-focused "track-target-test" analytic campaign on this issue. What are your plans?

Reviewed: McKinsey On Digital Marketing Metrics

Rob Schmults pointed me to an article in the latest issue of the McKinsey Quarterly titled, "How Poor Metrics Undermine Digital Marketing". The article summarizes findings from a June 2008 McKinsey survey of 340 leading marketers. The authors' take: "Hobbled by nascent technologies, inconsistent metrics, and a reliance on outdated media models, marketers are failing to tap the digital world’s full power."

My summary of their landscape:

1) The vanguard -- firms measuring more rigorously report greater satisfaction with digital marketing results;

2)The leading edge -- the frontier for competitive differentiation is now in online-offline optimization; and

3)The bleeding edge -- some firms are now mapping customers' relationships with each other to figure out influence networks and target offers accordingly (shades of this). For example,

McKinsey research on telephone users’ social networks suggests that even they can be measured to allocate marketing budgets more successfully. One telecom company, for example, has learned how to retain phone customers by assessing the strength of the relationships among them. The company used call patterns, changes in call volumes, types of payment (prepaid or contract), handset types, and other traits to identify customers likely to leave for another carrier. Meanwhile, it constructed a diagram of their social ties, derived from the people they called, the people those people called, and how often. In general, the more closely anyone was tied to someone who unsubscribed, the more likely that person was to unsubscribe in turn. In this way, the telecom company improved its churn prediction model by 50 percent. Moreover, by identifying the most influential potential churners and working to retain them with new services and price plans, the company not only retained a quarter of them but also reduced the churn rate within their social networks by almost 40 percent.

My take:

1) I disagree that we're hobbled by nascent technologies. The capability of today's tools significantly exceeds our effective use of them. What's missing is the hard work of education and training on how to use these tools in the context of supporting high-priority decisions, and the maintenance of associated queries, models, algorithms, data sets, tagging schemes, etc.

2)I agree that metrics are inconsistent -- both inside and across organizations. What's missing inside most firms is a shared understanding of how different target segments use / want to use multiple channels to discover, evaluate, and buy, and then collaboration within firms to maximize the outcome. For example, it's becoming clear that online and offline channels frequently complement each other (the authors offer stats on exactly how much that's true for different categories), and yet in many cases firms manage stores and direct/ e-channels as different businesses.

3)While it's useful as a high-level temperature check on where firms are on this issue, some of the conclusions are insufficiently nuanced. For example, the authors write,

When we asked respondents how they gauge the effectiveness of their digital-brand-building efforts and direct response advertising, their answers revealed a startling failure to measure. Only half of the respondents’ companies use even the most basic of metrics—the click-through rate—to evaluate the impact of direct-response advertising.

A finer-grained view of this would be that click-through rates for display ad campaigns have been heavily discredited lately as a primary metric; more sophisticated approaches today seek to correlate display ad impressions with searches and web traffic. A recent MITX session I attended on measuring brand impact online (writeup to follow) examined the state of play here helpfully. My guess is that there are shades of meaning behind the survey responses that might be mined usefully.

An interesting article. Certainly makes the case for greater attention to marketing analytics, and for investing beyond the tools themselves.