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Facebook Email Targeting & CRM Retargeting: Important New Tools for Marketers

1 Oct

Email marketing is a delicate art. In today’s world, fewer than 1/5 of recipients will open a commercial email message. For every 10 people who click on an email link, one person permanently opts out. While new subscribers are likely to open and click, results fall-off by 65% or more within just 4 months of email list subscription.

For most marketing organizations, email lists are full of high-potential contacts who no longer wish to receive email. In B2B, this is particularly an issue in businesses with  long sales cycles and high levels of lifetime customer value. While a prospect may be interested in a product or solution, they may not want to receive any commercial email.

A few weeks ago, Facebook rolled out a new advertising feature that allows marketers to display ads to targeted recipients selected via email address, phone number, or Facebook user ID. The new feature allows a self-service advertiser to upload an encrypted list of 20 or more contacts with the ad they want to show. Facebook will automatically target the supplied ad to the specified contacts.

This type of marketing, often referred to as CRM retargeting, allows advertisers to invest in building awareness or driving conversion within a known group of contacts. A large IT provider, for example, could drive an online campaign targeting known CIO’s who arbitrate buying decisions for their firms. A telecom company could market new devices to customers on expired contracts. Concert promoters can promote shows to people who have purchased tickets in the past. And all of this can be done using a prospect’s email address or phone number but without sending an email.

For B2B marketers focused on nurture marketing or content marketing, CRM retargeting enables marketers to reach prospects with relevant messages and content through an additional channel. It makes is possible to invest in advertising specifically targeting people who would prefer to not receive email. For companies with very large accounts, it would be possible to build account-targeted campaigns that deliver a unique message to representatives of a specific company. For companies looking to build a Facebook follower base, the new model allows them to promote their brands directly to a list of customers or fans who are most likely to engage online.

While others have attempted to use email as a filtering method for display advertising, two things makes Facebook’s new service unique: a billion member reach and a collection of multiple address for many of their members. For people with multiple addresses — work, home, school — Facebook is likely to have a match for whatever address might be in your CRM system.

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Predictive Analytics Will Transform B2B Sales & Marketing Execution

11 Sep

Consumer marketers have become adept at driving revenue based on predictive analytics. Potential customers are routinely scored on a wide variety of attributes from lifestyle to promotion receptiveness.  These scores allow consumers to be  segmented into groups based on shared interests, purchase likelihood, and total buying power. By starting with highly differentiated segments, marketers can design programs that are highly relevant and effective.

This is not the way that B2B sales and marketing works in most organizations today.

Yet, B2B is a ripe environment for predictive analytics: selling costs are high, sales probability is low, and resources are very expensive. While the language of B2B marketing and sales is full of references to probability — customer funnels, response rates, conversion rates, close rates, call-to-close ratios — it’s rare to see B2B organizations leverage prospect and customer data to score customer attributes, build discrete segments, and allocate resources to maximize the conversion and revenue.

But all of this is about to change. Over the next five years, common consumer marketing techniques will find a happy home in many B2B marketing and sales organizations.

Here are 6 reasons why:

  • Electronic sales processes are creating massive amounts of useful data: Today, B2B buyers spend more time interacting with companies online than they do with sales people in person or over the phone. For every successful sales call they attend, a typical prospect may spend hours interacting with content, reading forums and blogs, and testing sample products. In today’s world, every buyer action leaves a trail of digital clues that signal their context, needs, purpose, and intent.
  • Prospect attributes can be easily deduced from observable data: Most B2B organizations with CRM and content marketing capabilities have enough data to score prospects on purchase probability, likely problems or interests, and potential solution needs.
  • Relevancy matters: Even as the typical portfolio of products and solutions becomes more varied and complex, B2B sales and marketing messages tend to be narrow and simplistic. The patterns that work most consistently are destined to be forever repeated. For prospects, this means that they are often hit with messages and a pitch that ignore the nuance of their particular needs and segmentation. For many prospects, this is a turn-off that is difficult to reverse.
  • Sales & marketing funnels are based on probability: Typically, 2% of targets respond to a marketing campaign, 60% of leads are accepted by sales, 50% of accepted leads become opportunities, and 25% of opportunities close. When you look at the full marketing and sales funnel, a pathetic 1:667 targets becomes a closed deal. Using predictive analytics to improve any stage of the funnel has the potential to create incredible value. Continue reading →

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The Frightening Science of Prediction: How Target & 10 Others Make Money Predicting Your Next Life Event

6 Sep

If you are planning to go out tonight to play billiards at a bar in Montreal called Sharx, you might want to pay with cash. Predictive analytics from Canadian Tire demonstrated that Sharx customers are the more likely to default on credit than patrons of any other drinking establishment in Canada.

The analysis by Canadian Tire, now a decade old, marked the beginning of a wave of predictive analytics that now has companies trying to guess your next move — no matter how private it may be. Are you going to get married? Are you having a baby? Are you likely to get a divorce? Might you run into financial problems? Are you changing jobs or moving cities? Who are you going to vote for? Who are you likely to buy something from? What big purchase are you likely to make next? When will you get sick? How soon might you die?

If there is value in the answer to any of these questions, there is likely a company that is actively trying to predict the answer based on the data they have on you. As credit cards and loyalty cards have become omnipresent, more and more companies are now able to mine deeply personal data patterns to predict private behavior.  According to the New York Times, “Almost every major retailer, from grocery chains to investment banks to the U.S. Postal Service, has a ‘predictive analytics’ department devoted to understanding not just consumers’ shopping habits but also their personal habits, so as to more efficiently market to them.”

Here are 11 real examples of how companies are trying to predict your next life event:

1. Predicting Pregnancy (Target): Target uses a statistical model to score every female customer on the likelihood that they are pregnant. It can accurately predict when a shopper is pregnant early in the pregnancy and her rough due date. As reported in the New York Times, Target’s data scientist is “able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a ‘pregnancy prediction’ score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy.” According to a Target data scientist who was quickly banned by the Company from talking to the press, “We knew that if we could identify them in their second trimester, there’s a good chance we could capture them for years . . . As soon as we get them buying diapers from us, they’re going to start buying everything else too.”

2. Predicting Divorce (Credit Card Companies): In the book Super Crunchers, a Yale professor describes how a major credit card provider uses purchase data to predict divorce, which in turn, helps the company predict potential future credit problems.

3.  Predicting Financial Problems (Canadian Tire): According to the Daily Beast: “Cardholders who purchased carbon-monoxide detectors, premium birdseed, and felt pads for the bottoms of their chair legs rarely missed a payment. On the other hand, those who bought cheap motor oil and visited a Montreal pool bar called ‘Sharx’ were a higher risk. ‘If you show us what you buy, we can tell you who you are, maybe even better than you know yourself,’ a former Canadian Tire exec said.”

4. Predicting Your Next Vote (Obama & Romney Campaigns): Both major parties maintain broad voter databases appended with detailed demographic information. Using psychographic profiling, they are able to predict who you will vote for, how likely you are to go to the polls, and the potential for them to change your vote. Using this data, they are able to drive targeted media strategies and send volunteers to the right doors to maximize impact on the election. As reported in the Washington Post, “If you use Spotify to listen to music, Tumblr to consume content or Buzzfeed to keep up on the latest in social media, you are almost certainly a vote for President Obama. If you buy things on eBay, play FarmVille or search the web with Bing, you tend to favor former Massachusetts governor Mitt Romney.”

5. Predicting When You Will Switch to Fedex (UPS): UPS uses data analytics to predict when customers are at risk of abandoning the company and switching to one of its competitors. Whenever a potential switcher is identified, the company tries to prevent the loss with a phone call from a salesperson.

6. Predicting How Influential You Are (The Palms): Third party companies like Klout have built complex algorithms for assessing the social media impact of an individual. If you complain online, it’s your Klout score that will often determine the response. But now, companies like The Palms and Gilt Groupe are using these social media influence predictors to differentiate between customers. According to AdAge, “The Palms’ chief marketing officer, Jason Gastwirth, is currently building out ‘The Klout Klub,’ which ‘will allow high-ranking influencers to experience Palms’ impressive set of amenities in hopes that these influencers will want to communicate their positive experience to their followers.’ The Palms is already pulling in data from Klout and referring to it as part of their reservations process.”

7. Predicting How Much Money You are Willing to Lose (Harrah’s): According to the Daily Beast, “With its ‘Total Rewards’ card, Harrah’s casinos track everything that players win and lose, in real time, and then analyze their demographic information to calculate their ‘pain point’—the maximum amount of money they’re likely to be willing to lose and still come back to the casino in the future. Players who get too close to their pain point are likely to be offered a free dinner that gets them off the casino floor.”

Continue reading →

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The Nurture Fallacy: 5 E-Nurture Marketing Myths

16 Aug

Marketing automation companies have built a big business by creating tools for electronic “nurture” programs. Now, B2B marketers around the world are executing “e-nurture” programs designed to take prospects on a multi-step journey designed to increase prospect education and awareness, and ultimately, to lead prospects to buy.

It’s not uncommon to see B2B marketers execute complex drip and trigger campaigns with seemingly endless tracks and branches. In some organizations, nurture complexity has outstripped the ability of charting tools to diagram the planned  communication paths.

While marketers must focus on the customer journey, the current e-nurture fad fails to deliver on the value that it promises. Here are the five commonly held beliefs that I believe to be myths:

Myth # 1: “You can take prospects on an email journey”

While email remains an invaluable tool for marketing and demand generation, it is a horrible tool for guiding prospects on a linear educational journey. Here’s why: only 10.8% of email is ever opened, and only 30% of mail that is opened is actually read (the rest is skimmed).

Most nurture campaigns are built on the assumption that a prospect will internalize a core message or idea and will progress on the electronic customer journey from message to message. The fact is that very little commercial email is read, very few ideas are internalized, and very few people are persuaded by content delivered through email. While some portion of people who open may click through and interact with online content, that proportion is almost always a small single digit percentage of the overall campaign audience. By the time the next message arrives, the educational benefits of the previous message are almost always forgotten.

Myth # 2: “Content should be sequenced along an educational path”

To maximize sales conversion, email campaigns should promote the best content (based on conversion rate) vs. optimizing content to follow a progressive educational path. Nurture campaigns should be focused on sequencing content based on effectiveness by first merchandising the content with the highest impact that hasn’t yet been accessed by a particular prospect. It’s common sense: sequencing content based on performance vs educational narrative will always drive better results.

Myth # 3: “The more tracks and steps, the better”

As marketers build teams and programs around nurture strategies, they often drift towards micro-segmentation of the prospect database based on interest and sales stage. The result is an endless tree of options and content as prospect interest evolves and sales stages change.

For marketing and sales, the typical result is painful complexity and a proliferation of content required to address every interest/stage permutation. In most companies, a few pieces of content do the real heavy lifting and have the biggest impact on persuasion and conversion. A proliferation of nurture segments dilutes the impact of the best content and creates heavy demands for new content that inevitably underperforms and quickly becomes out-of-date.

Myth # 4: “Prospect activity tracking is the secret to an effective nurture program “

Since only 10.8% of email is opened, a basic nurture practice is to resend messages to people who ignore the first message to try to get their attention a second, third, or fourth time. Continue reading →

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