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Effective Data-Driven Decision Making for High Performance Demand Generationor demand generation 20130307
 

Effective Data-Driven Decision Making for High Performance Demand Generationor demand generation 20130307

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You cannot rely on intuition and experience alone to make critical marketing investments. Data can help us optimize our marketing efforts, predict results, justify spend and validate our impact and ...

You cannot rely on intuition and experience alone to make critical marketing investments. Data can help us optimize our marketing efforts, predict results, justify spend and validate our impact and influence on revenue. But to do that, you need to have the right data.

This webinar discusses how to capture the metrics you need and use them to make decisions that will deliver significant performance gains.

Covered in this presentation:
1. Key metrics every B2B marketer must focus on
2. A framework for setting up a solid data foundation
3. The difference between data and insights
4. When and how to act on data-driven insights

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  • We work with marketing to understand their needs—translate that into technology
  • Why Data-Driven strategies?Challenges facing the MarketerImproper tracking Broken linkagesData Consistency
  • Albert Einstein once said “information is not knowledge” and data without context is just organized information.In essence, data is just people doing stuff.The true value of data is far beyond obsessions with key performance metrics.For most businesses, it’s about extracting insights to create value that has the potential to drive innovation to improve products and services.In fact, more companies are shifting their focus from traditional business intelligence (BI) to predictive analytics – using historical data to predict future events.
  • Nerds on Wall Street tells the tale of the ongoing technological transformation of the world's financial markets. The impact of technology on investing is profound, and author David Leinweber provides readers with an overview of where we were just a few short years ago, and where we are going. Being a successful investor today and tomorrow--individual or institutional--involves more than stock picking, asset allocation, or market timing: it involves technology. And Leinweber helps readers go beyond the numbers to see exactly how this technology has become more responsible for managing modern markets. In essence, the financial game has changed and will continue to change due entirely to technology. The new "players," human or otherwise, offer investors opportunities and dangers. With this intriguing and entertaining book, Leinweber shows where technology on Wall Street has been, what it has meant, and how it will impact the markets of tomorrow.
  • Netflix is pulling back the curtain in a two-part blog post to reveal some behind-the-scenes workings, such as the fact that 75% of the content watched on the service comes from its recommendation engine.No, the company doesn't reveal its recommendation algorithm (which we imagine to be quite complex), but it does emphasize that "everything is a recommendation," from a standard Top 10 to those quirky super-specific genres, like "Imaginative Time Travel Movies From The 1980s."When Netflix displays rows of movies in those genres, it's personalizing its service three times: "the choice of genre itself, the subset of titles selected within that genre, and the ranking of those titles."With the focus on being as personal as possible, it makes sense that such a high percentage of Netflix viewership comes directly from its recommendation algorithm.Read more: http://articles.businessinsider.com/2012-04-09/tech/31310576_1_netflix-personalizing-algorithm#ixzz2MmO11yIh
  • There's no doubt that we're in the midst of a sea change for marketing. For one thing, only a few years ago the average person was afraid of technology—now they're terrified of being without it. We're moving towards what I've referred to in the past as a "quantified society" where many aspects of our lives are optimized algorithmically.That means everything we do leaves a digital breadcrumb trail, and that trail is available for marketers to analyze.But it's not going to be that simple. For one thing, even with all of this data, it's unlikely most businesses will act wisely upon it. I wrote about this a year or so ago in a post entitled "there's no such thing as Big Data," arguing that big companies can't handle the cultural shifts required.Look at Blockbuster, for example: it had all the advantages over Netflix. It had customer data, rental histories, even agreements with studios. But it couldn't act on that information.That said, we know that many enterprises do understand the importance of continuous, disciplined learning. In the book we cite examples of Lockheed Martin, Proctor & Gamble, EMI, Frito-Lay and others who've taken a Lean Analytics approach to innovation, with excellent results.The real issue is this: once upon a time, a business leader was someone who could convince others to act in the absence of information. Now, we're swimming in information. The leader is now the person who knows what questions to ask. That's a big change, and it'll mean replacing executives who got to the boardroom by being convincing, rather than right.
  • In today’s working environment we have to deal with receiving information from many different sources, in multiple formats, which we are struggling to manage, digest and navigate the information to get to what is relevant. Something as simple as searching for information can waste a lot of time and have a big effect on our own productivity, and in turn can affect performance and job satisfaction.We decided to conduct some research into this issue of information overload, with the aim of quantifying how much of a problem this is proving for office workers and consequently businesses today. Our survey was conducted by One Poll to office workers across the UK, Sweden and Holland, and asked a series of questions to find out how much information we receive on a daily basis and from which sources. The results of this research have provided some very interesting insights into around how the information that faces us on a daily basis is affecting employee efficiency and ultimately costing businesses.
  • sheds some light on the war in marketing between the “humanists” of Don Draper’s world and the “quants” of the digital marketing revolution.While the rise of search battered the humanists, it also laid a trap that the quants are falling into now. It led to the belief that with enough data, all of advertising could turn into quantifiable science.This came with a punishing downside. It banished faith from the advertising equation. For generations, Mad Men had thrived on widespread trust that their jingles and slogans altered consumers’ behavior. Thankfully for them, there was little data to prove them wrong.But in an industry run remorselessly by numbers, the expectations have flipped. Advertising companies now face pressure to deliver statistical evidence of their success. When they come up short, offering anecdotes in place of numbers, the markets punish them. Faith has given way to doubt.This leads to exasperation, because in a server farm packed with social data, it’s hard to know what to count. What’s the value of a Facebook “like” or a Twitter follower? What do you measure to find out?In this way, marketing resembles other hot spots of data research, including health careand genomics, astronomy. In each one, scientists are combing through petabytes of data, trying to discern whether certain genes or groups of neurons cause something or simply correlate with it. It’s not clear, because these are immensely complex systems with millions of variables — much like our social networks.Even as researchers swim in data that previous generations would have swooned over, they struggle to answer crucial questions regarding cause and effect. What action can I take to get the response I want?
  • Volume: Amplifies and creates reach
  • Velocity: Rapid insights provide competitive advantage For many applications, the speed of data creation is even more important than the volume. Real-time or nearly real-time information makes it possible for a company to be much more agile than its competitors. For instance, our colleague Alex “Sandy” Pentland and his group at the MIT Media Lab used location data from mobile phones to infer how many people were in Macy’s parking lots on Black Friday—the start of the Christmas shopping season in the United States. This made it possible to estimate the retailer’s sales on that critical day even before Macy’s itself had recorded those sales. Rapid insights like that can provide an obvious competitive advantage to Wall Street analysts and Main Street managers.
  • As more and more business activity is digitized, new sources of information and ever-cheaper equipment combine to bring us into a new era: one in which large amounts of digital information exist on virtually any topic of interest to a business. Mobile phones, online shopping, social networks, electronic communication, GPS, and instrumented machinery all produce torrents of data as a by-product of their ordinary operations. Each of us is now a walking data generator. The data available are often unstructured—not organized in a database—and unwieldy, but there’s a huge amount of signal in the noise, simply waiting to be released. Analytics brought rigorous techniques to decision making; big data is at once simpler and more powerful. As Google’s director of research, Peter Norvig, puts it: “We don’t have better algorithms. We just have more data.”
  • Social media data from sources such as Twitter, blogs, and forums  Internal data sources such as marketing data, customer databasesExtended Customer Behaviour •What types of profiles exist and what value can be generated from understanding these profiles? How do customers use your products and services? Understand and drive insights on product quality and sentiments Campaign Effects What impact has a Campaign had on customers behaviour at the individual level? Advanced analytics technologies (unstructured data analytics, real-time, and predictive analytics)
  • 20% of marketers don’t measure marketing-sourced leads at all30% are not tracking advanced metrics such as marketing-sourced opportunities35% of marketers surveyed are not using lead nurturing for less qualified leadsNearly 30% are lacking the tools needed to track leads throughout the sales cycle60% do not currently have or are unsure if their company has a specific strategy for handling the challenges of Big Data81% feel that they are either somewhat or not very prepared when it comes to the new rules and regulations of marketing data governance50% say that skill sets are changing, especially with the growth of social and mobile channelsThough marketers need to show that technology investments deliver business impact, most focus primarily on basic response metrics (80%), such as email opens and clicks, whereas roughly half that proportion focus on incremental improvements to lead generation (41%) and revenue (40%).
  • CEOs and boards don’t care about 99% of the metrics that marketers track – but they do care about revenue and profit growth. There are two primary categories of financial metrics that directly affect revenue and profits:• Revenue Metrics: Marketing’s aggregate impact on company revenue • Marketing Program Performance Metrics: The incremental contribution of individual marketing programs
  • There is so much data coming in at such a high velocity in all types of complexity that this phenomenal we called big data is now a problem for most businesses.In fact, there are so many challenges in dealing with big data that it’s often hard to process let alone understand.This is especially true for any business that engages with digital advertising or online marketing.sheds some light on the war in marketing between the “humanists” of Don Draper’s world and the “quants” of the digital marketing revolution.While the rise of search battered the humanists, it also laid a trap that the quants are falling into now. It led to the belief that with enough data, all of advertising could turn into quantifiable science.This came with a punishing downside. It banished faith from the advertising equation. For generations, Mad Men had thrived on widespread trust that their jingles and slogans altered consumers’ behavior. Thankfully for them, there was little data to prove them wrong.But in an industry run remorselessly by numbers, the expectations have flipped. Advertising companies now face pressure to deliver statistical evidence of their success. When they come up short, offering anecdotes in place of numbers, the markets punish them. Faith has given way to doubt.This leads to exasperation, because in a server farm packed with social data, it’s hard to know what to count. What’s the value of a Facebook “like” or a Twitter follower? What do you measure to find out?In this way, marketing resembles other hot spots of data research, including health careand genomics, astronomy. In each one, scientists are combing through petabytes of data, trying to discern whether certain genes or groups of neurons cause something or simply correlate with it. It’s not clear, because these are immensely complex systems with millions of variables — much like our social networks.Even as researchers swim in data that previous generations would have swooned over, they struggle to answer crucial questions regarding cause and effect. What action can I take to get the response I want?
  • This is why it’s important to maintain focus on business objectives in addition to all the online marketing tactics because like the author of the book Antifragile, NassimTaleb wrote, “We’re more fooled by noise than ever before, and it’s because of a nasty phenomenon called “big data.” With big data, researchers have brought cherry-picking to an industrial level. Modernity provides too many variables, but too little data per variable. So the spurious relationships grow much, much faster than real information. In other words: Big data may mean more information, but it also means more false information.”It’s meaningless if we have the means to analyze the data but the data is wrong to start with.4 Pillars of Insight TransformationIt’s Not About Knowledge But How You Use It 1. RelevancyHow do we use customer intelligence in our dialogue with the customer so products, services, messages, and offers are presented in such a way that is truly relevant to the customer? This means going beyond looking at the last transaction or information from constrained data fields. Take for example a customer service rep from a catalog company who made notations about a customer’s purchase for their daughter’s 12th birthday the previous year. This year’s call in the same time period allowed the support and cross-sale initiatives to be highly relevant to the customer.2. Context How does our view of the customer intelligence change when we learn more about why the customer has exhibited previous behaviors and what their true underlying needs are today? Take our same example and think about how differently the rep’s conversation is based on knowing the customer is gift shopping instead of personally shopping. The context of a repeat birthday shopper should also set a trigger for future contacts.3. TimingHow do we connect customer intelligence with the critical aspect of timing to benefit from reaching customers in the right window of opportunity, creating an appropriate sense of urgency, making contact at the right point in the decision-making process, or factoring in the seasonality and cycles of customer needs? Besides the obvious timing of the birthday purchase we’ve established for our example, we can also factor in the daughter’s age and the season of each purchase to make specific recommendations for the customer.4. Emotive FactorsHow do we enhance our customer intelligence to understand and benefit from the underlying emotive factors that lead to what the data would determine are irrational or unanticipated decisions? Knowing the importance of a birthday purchase for a close family member is valuable insight. Through the rep’s dialogue with the customer, it may also be possible to capture additional emotive factors such as how comfortable the customer is making purchases for someone in this age group. The interaction is different once it is known that this is a stressful purchase where the parent depends on the helpful guidance of the rep.
  • 1. ConversionsYour internet marketing campaign is supposed to do something that will ultimately impact your organization – generate leads, or sales, or votes, or something similar. I’m not talking about visits, here. A visitor is great, but does nothing for you if they don’t somehow act in your favor.So-so implementation: The simplest way to track conversions is over time. If you have no traffic reporting system in place, you can still track conversions before, during and after you launch a particular campaign, and see what difference it made. This isn’t precise, but it works.Good implementation: Again, if you don’t have reporting in place, you can still do something to separate conversions driven by your internet marketing strategy from those that are generated elsewhere. You can have a special coupon, or a separate 800 number, or a different response code.Best implementation: Set up a traffic reporting tool that includes conversion tracking. Google Analytics is my favorite (it’s free, but very powerful). Omniture is the Mercedes of the bunch. You can learn how to set up conversion or goal tracking on my blog, here, or from the tutorials each reporting system provider has on their sites. It’s not that hard, I promise. And, with this set-up, you’ll be able to track conversion sources (pay per click versus organic search versus e-mail, for example), which is important as you dig deeper (see below).
  • How long does it take to create a campaign?●When is your message reaching your subscribers?●Are your messages timely?●Are you able to send the right message at the right time?3. TimingHow do we connect customer intelligence with the critical aspect of timing to benefit from reaching customers in the right window of opportunity, creating an appropriate sense of urgency, making contact at the right point in the decision-making process, or factoring in the seasonality and cycles of customer needs? Besides the obvious timing of the birthday purchase we’ve established for our example, we can also factor in the daughter’s age and the season of each purchase to make specific recommendations for the customer.
  • For most businesses, prospect and customer data lives in many different systems and databases — CRM, email marketing databases, call center history logs, order entry systems, point of sale systems and sales databases to name a few.A big challenge in marketing analytics is integrating data from various sources. Marketing data invariably spreads across over various systems and databases. A big chunk of it may actually be offline or even on paper. The marketer has to collect the data from various sources such as customer relationship management software, call center logs, email databases, order entry systems, point of sale terminal systems and sales databases. The marketer’s task becomes further complicated by the need to collect data from all possible sources without duplicating the data
  • Skill sets. Quants., head for numbers
  • Just like you wouldn’t expect a musician to compose a song without a tune, or a restaurant to open without a menu, you can’t expect to develop a strategy or execute a tactic using data without knowing what you want to achieve.This is at the core of any data-driven performance marketing – makes decision based on analysis to prove or disprove hypothesis.4. Ask, 'Do you have data to support that?'Start every project or request with that question. When considering a specific marketing channel or approach, ask for data that suggests it will work. At the very least, ask how you will know if it worked: What will you measure?Taking this approach encourages marketers to think about how they create value for the company at a time when marketing channels are continually evolving and resources are stretched.When you have hard decisions to make, data and analysis allow you to base those decisions on facts and create the right balance in your marketing efforts. What's more, analytics will help you monetize your marketing investments. Say, for example, that you have traditionally attended a large number of tradeshows and conferences—which are costly and resource intensive. Now you have the opportunity to reach even larger audiences through digital channels. But how do you create the right balance? Analytics will provide you with insight about the value of each marketing activity, the audience you reach with it, its historical and potential returns, and how to use multiple channels for optimum outcomes.Linking the marketing activity to the expected value will provide you with the ability to make fact-based investment decisions.
  • If activity, cost, and quantity aren’t the right metrics to use, what are? Anything that speaks to the CFO’s areas of primary concern: revenue, margin, profit, cash flow, ROI, shareholder value – in other words, your company’s ability to generate more profits and faster growth than your competitors. This is what Roy Young and Allen Weiss of MarketingProfs call “speaking the language of business”
  • CEOs and boards don’t care about 99% of the metrics that marketers track – but they do care about revenue and profit growth. If activity, cost, and quantity aren’t the right metrics to use, what are? Anything that speaks to the CFO’s areas of primary concern: revenue, margin, profit, cash flow, ROI, shareholder value – in other words, your company’s ability to generate more profits and faster growth than your competitors. This is what Roy Young and Allen Weiss of MarketingProfs call “speaking the language of business”There are two primary categories of financial metrics that directly affect revenue and profits: • Revenue Metrics: Marketing’s aggregate impact on company revenue • Marketing Program Performance Metrics: The incremental contribution of individual marketing programs
  • 1. ConversionsYour internet marketing campaign is supposed to do something that will ultimately impact your organization – generate leads, or sales, or votes, or something similar. I’m not talking about visits, here. A visitor is great, but does nothing for you if they don’t somehow act in your favor.So-so implementation: The simplest way to track conversions is over time. If you have no traffic reporting system in place, you can still track conversions before, during and after you launch a particular campaign, and see what difference it made. This isn’t precise, but it works.Good implementation: Again, if you don’t have reporting in place, you can still do something to separate conversions driven by your internet marketing strategy from those that are generated elsewhere. You can have a special coupon, or a separate 800 number, or a different response code.Best implementation: Set up a traffic reporting tool that includes conversion tracking. Google Analytics is my favorite (it’s free, but very powerful). Omniture is the Mercedes of the bunch. You can learn how to set up conversion or goal tracking on my blog, here, or from the tutorials each reporting system provider has on their sites. It’s not that hard, I promise. And, with this set-up, you’ll be able to track conversion sources (pay per click versus organic search versus e-mail, for example), which is important as you dig deeper (see below).2. SpendWhat are you spending to get those conversions? Better hope it’s less than they’re worth…So-so: Take the total amount spent over a day, week or month. Divide it by the number of conversions. Then take the total amount earned over the same period, and divide it by the number of conversions. If the latter is less than the former, you have some serious thinking to do.Good: Break it down by product. Do the same calculations, but product-by-product. That means you have to have some idea what you spent to market each product or category, though. Can you do it?Best: Use your analytics tool. Have a look at the actual value, down to the click, of every dollar you spend. Here’s a report in Google Analytics that’s telling me the per-visit value of every click, from every source. If I click on ‘google / organic’, I’ll be able to see the value of every click from every keyword. That data is priceless.3. AttentionOnce you’re measuring conversion, and cost per conversion, you want to focus on the attention you’re getting. That’s a combination of visits, return visits, page views per visit and the time spent on your site by the average visitor. Note that you have to have some form of traffic reporting in place to use any of these options.So-so: Measure unique visitors and page views per visitor. A unique visitor is any one person coming to your site in a given time period, any number of times. So, if I come to your site 34 times in one month, I’m still 1 unique visitor. More page views per unique visitor means you’re getting more attention. But this number is far from perfect, because some technologies (Flash, AJAX, etc.) aren’t measured as page views. So you may under-record page views.Good: Measure unique visitors, page views per visitor, and time on site. By adding in time on site you get a more ‘tech-proof’ attention metric. If page views drop, but time on site climbs, you’re likely doing just fine.Best: Measure unique visitors, page views per visitor, and time on site. But break it down by the referring source, as well. Now you’re measuring the quality of traffic from each site or ad that generated visits. In the report below, I know that Google is sending me higher-quality traffic, even though it generates fewer pages per visit than StumbleUpon, because the average Google visitor is spending over 2 minutes on my site:4. Bounce RateNo, I haven’t drifted into basketball. The bounce rate is the number of people that land on one page of your site, then leave without visiting any other pages. Again, you have to have some form of traffic reporting to measure this.Best: There’s only one option, really. Pull up your ‘content’ or ‘pages’ report and look at the Bounce Rate column. In the example below, my home page is actually the worst. Gotta do something about that…5. ErrorsYou must track errors! If you don’t, how will you know when something goes wrong?So-so: Get a monthly or weekly report of ’404′ (also known as a page not found) errors. Your hosting provider likely has a report they can give you. You can use Google Analytics to do this by following these instructions.Good: Get a weekly report of both 404 and ’500′ errors. A 500 error indicates that something on your site actually broke. It’s different from a 404 error, which just reports that someone tried to find something that wasn’t there in the first place.Best: Track both 404 and 500 errors every day, or every hour. Here’s why: Let’s say a site that gets 40,000 visitors per day reviews your product. That’s good! They put a link on their site to yours. That’s good, too! But the link they put in place is incorrect. That’s bad. If you’re receiving 404 error reports every hour, then you’ll find out, and you can address the problem. If you don’t, then 40,000 people may pass you by, and you’ll never know. Ouch.6. Onsite Search TermsTrack the phrases folks type into your onsite search tool. If you can focus your site on the top 10% or so of these phrases, you’ll see an immediate lift in conversion rates.Best: Only one way to do this – through your traffic reporting tool. You may be able to get a report from the search tool itself, but it’s unlikely. You can see my tutorial on measuring onsite search traffic here.7. Bailout RatesIf you have a shopping cart or another multiple-form process, you need to know when and where folks give up.Best: Again, the only easy way to do this is through your traffic reporting software. The exact procedure varies. Look for a report called something like ‘goal funnel reporting’ or ‘cart abandonment’ and you’re in the right place. You’ll need to set it up, defining each step in the process. The end result will look like this:
  • Lenskold Group points out that there are also different types of metrics in each category, based on time: Past: How did we do? Present: How are we doing? Future: How will we do? These questions break into three corresponding metric categories: Business Performance Metrics & KPIs How did we do last week? Last month? Last quarter? These are the most common reporting metrics that you share with fellow executives, often on a dashboard. They are mostly BACKWARDS looking metrics. Diagnostic Metrics What is working, and what can work better? These metrics deliver insight into your CURRENT performance, often by comparing against historical data trends and competitor and marketplace benchmarks. Leading Indicators How will we be doing in the future? These metrics help you look FORWARD and forecast future results. (See Section 6, Forecasting.)
  • WHERE METRICS GO WRONG There are literally hundreds of marketing metrics to choose from, and almost all of them measure something of value. The problem is that most of them relate very little to the metrics that concern a CFO, CEO and board member. Of course, it’s okay to track some of these metrics internally within your department if they will help you make better marketing decisions. But it’s best to avoid sharing them with other executives unless you’ve previously established why they matter. Vanity metrics Too often, marketers rely on “feel good” measurements to justify their marketing spend. Instead of pursuing metrics that measure business outcomes and improve marketing performance and profitability, they opt for metrics that sound good and impress people. Some common examples include press release impressions, Facebook “Likes”, and names gathered at trade shows. Measuring what is easy When it is difficult to measure revenue and profit, marketers often end up using metrics that stand in for those numbers. This can be OK in some situations, but it raises the question in the mind of fellow executives whether those metrics accurately reflect the financial metrics they really want to know about. This forces the marketer to justify the relationship and can put a strain on marketing’s credibility. Focusing on quantity, not quality According to a 2010 Lenskold Group / emedia Lead Generation Marketing ROI Study, the number one metric used by lead generation marketers is lead quantity, whereas barely half of marketers measure lead quality. Focusing on quantity without also measuring quality can lead to programs that look good initially but don’t deliver profits. (To take this idea to the extreme, the phone book is an abundant source of “leads” if you only measure quantity, not quality.) Activity, not results Marketing activity is easy to see and measure (costs going out the door), but marketing results are hard to measure. In contrast, sales activity is hard to measure, but sales results (revenue coming in) are easy to measure. Is it any wonder, then, that sales tends to get the credit for revenue, but marketing is perceived as a cost center? Efficiency instead of effectiveness In a related point, Kathryn Roy of Precision Thinking suggests paying attention to the difference between effectiveness metrics (doing the right things) and efficiency metrics (doing – possibly the wrong – things well). For example, having a packed event is no good if it’s full of all the wrong people. Effectiveness convinces sales, finance and senior management that marketing delivers quantifiable value. Efficiency metrics are likely to produce questions from the CFO and other financially-oriented executives; they will be no defense against efforts to prune your budget in difficult times.
  • Set goals!
  •  Follow the data. Data highlights behavioral patterns. That's the mantra for 2013. Marketers have found most events are predictable using statistical analysis, even when it comes down to word choice in comments and recommendations. Data will become the most critical driver of the information age, similar to oil in the industrial age, but many marketers are ill-prepared to make decisions in real time.Arvind J. Singh, co-founder and CEO of Utopia, a global data lifecycle consulting-and-services firm, compares mining oil to extract into gasoline that makes cars run, with mining raw data to extract into actionable information that improves marketing campaigns.Both oil and data require expertise to extract benefits from raw resources. But usnlike oil, data doesn't evaporate once used. The value continues to grow as marketers add new pieces of data, Singh says. "Similar to the way oil fuels an important piece of the industrial revolution, data fuels an important piece of the information age," he says. "The difference is one grows in value, gains strength and reusable, while the other gets spent."Singh calls data the building blocks that develop insights, and suggests marketers need to follow and manage information lifecycles.
  • It goes without saying that data integrity is essential for marketing analytics, not just attribution.The point is that whether you’re doing marketing, we need reliable data to help us make better decisions.4. Ask, 'Do you have data to support that?'Start every project or request with that question. When considering a specific marketing channel or approach, ask for data that suggests it will work. At the very least, ask how you will know if it worked: What will you measure?Taking this approach encourages marketers to think about how they create value for the company at a time when marketing channels are continually evolving and resources are stretched.When you have hard decisions to make, data and analysis allow you to base those decisions on facts and create the right balance in your marketing efforts. What's more, analytics will help you monetize your marketing investments. Say, for example, that you have traditionally attended a large number of tradeshows and conferences—which are costly and resource intensive. Now you have the opportunity to reach even larger audiences through digital channels. But how do you create the right balance? Analytics will provide you with insight about the value of each marketing activity, the audience you reach with it, its historical and potential returns, and how to use multiple channels for optimum outcomes.Linking the marketing activity to the expected value will provide you with the ability to make fact-based investment decisions.Blatantly wrong informationWrong company relationshipSystem generated bad dataTypos, human errorAlso:Multiple email addresses for the same person:Two different emails that are not bouncing backChanged companies (employment)
  • Your data is like your 401(k): You need to manage it so it delivers the results you want. It needs to be accurate; otherwise, your analysis and ultimately your decisions could be flawed. Accordingly, you'll need to rebalance it every now and then: look for sources you don't need anymore or data that isn't providing value... and get rid of them; reinvest your resources where you're getting returns. Recently, in our marketing organization, we focused an initiative on data source performance, and we were able to eliminate the poorest-performing investments, which translated to cost savings and increased effectiveness.
  • Determine what data you need to create a holistic picture of your customer to help and create a master template for forms, lists
  •  Follow the data. Data highlights behavioral patterns. That's the mantra for 2013. Marketers have found most events are predictable using statistical analysis, even when it comes down to word choice in comments and recommendations. Data will become the most critical driver of the information age, similar to oil in the industrial age, but many marketers are ill-prepared to make decisions in real time.Arvind J. Singh, co-founder and CEO of Utopia, a global data lifecycle consulting-and-services firm, compares mining oil to extract into gasoline that makes cars run, with mining raw data to extract into actionable information that improves marketing campaigns.Both oil and data require expertise to extract benefits from raw resources. But usnlike oil, data doesn't evaporate once used. The value continues to grow as marketers add new pieces of data, Singh says. "Similar to the way oil fuels an important piece of the industrial revolution, data fuels an important piece of the information age," he says. "The difference is one grows in value, gains strength and reusable, while the other gets spent."Singh calls data the building blocks that develop insights, and suggests marketers need to follow and manage information lifecycles.
  • Create your own lead management model
  • Identify your touchpoints
  • It goes without saying that data integrity is essential for marketing analytics, not just attribution.You do attribution because you want to get to the bottom of your marketing efforts. It’s a complex process of giving credit to your paid, earned, and owned media. It’s about translating the value of your marketing programs.We’re talking about segmentation, media buying, content management, optimization, and a whole lot more!And don’t forget whatever metrics you’re tracking and measuring, they must align with business objectives, agreed upon across departments (or at least as many as possible).
  •  Follow the data. Data highlights behavioral patterns. That's the mantra for 2013. Marketers have found most events are predictable using statistical analysis, even when it comes down to word choice in comments and recommendations. Data will become the most critical driver of the information age, similar to oil in the industrial age, but many marketers are ill-prepared to make decisions in real time.Arvind J. Singh, co-founder and CEO of Utopia, a global data lifecycle consulting-and-services firm, compares mining oil to extract into gasoline that makes cars run, with mining raw data to extract into actionable information that improves marketing campaigns.Both oil and data require expertise to extract benefits from raw resources. But usnlike oil, data doesn't evaporate once used. The value continues to grow as marketers add new pieces of data, Singh says. "Similar to the way oil fuels an important piece of the industrial revolution, data fuels an important piece of the information age," he says. "The difference is one grows in value, gains strength and reusable, while the other gets spent."Singh calls data the building blocks that develop insights, and suggests marketers need to follow and manage information lifecycles.
  • Realize that you will need to understand technical infrastructure such as web hosting, data warehousing, and how data flows in and out of business infrastructure.In addition, recognize that every business utilizes a variety of applications behind the technical infrastructure.So make sure that you have some basic knowledge of how each of those applications work and what other tools are available to help you integrate more useful t data.
  • Give your marketers the freedom to test and learn so they can make intelligent decisions that will drive change. Optimization has a direct impact on results, and it will indirectly increase the confidence level of your marketers. Since we began applying marketing optimization techniques, our conversion rates have tripled on outbound marketing campaigns while associated communication costs are dropping. Our list size has shrunk 14%, opt-outs have dropped 20%, and click-through rates have jumped 25%. Together, all of that adds up to higher-quality leads, lower costs, and an improved customer/prospect experience.With millions of visitors on our website, analytics is critical to determining how we make the best use of a person's time on site. With scoring and nurturing efforts, we have experienced conversion rates at 20%–30%. Add the ability to integrate online chat capabilities, and we've seen even higher conversions; and, more important, we have enhanced the overall experience in real time.None of that could have happened if our marketers weren't comfortable testing, measuring, changing, and justifying marketing activities.Let analytics decide the best approach.

Effective Data-Driven Decision Making for High Performance Demand Generationor demand generation 20130307 Effective Data-Driven Decision Making for High Performance Demand Generationor demand generation 20130307 Presentation Transcript

  • Data-driven Strategies for Demand Generation A Digital Solutions Firm delivering Marketing and Technology SolutionsNew York . Toronto . Phoenix . Los Angeles . London. Dubai . New Delhi
  • Presenter Shawn De Souza Demand Generation Practice Director Background: Modern Marketer Savvy Technologist Expertise in B2B and B2C Areas of Specialization: SEO/SEM, Social, Mobile, Lead Management, Campaigns, CRM, Analytics 1
  • About eDynamiceDynamic is a digital consultancy that helps clients acquire andengage customers through cutting edge interactive solutionsExperienced. Founded in 1999Trusted. Diverse business critical projects delivered formid-size to Fortune 500 organizationsVersatile. Experience across diverse verticals, includingFinancial Services, Technology, Legal, Retail, Media &Publishing, Education, Travel and Hospitality and EnergyGlobal. Locations in United States, Canada, Middle-East andIndia 2
  • eDynamic supports key stages in the customer lifecycle 3
  • eDynamic empowers the marketerOur capabilities center around empowering the marketer duringthe entire customer lifecycle, from acquisition to engagement 4
  • Why Data? 5
  • 6Information is not knowledge - Albert Einstein
  • Weather Data – for Meteorologists 7
  • Weather Data – for Meteorologists 8
  • Weather data for you and me 9
  • Stock Markets 10
  • New(er) Technologies 11
  • 12
  • 13
  • The Data Tsunam 14
  • VolumeAmplifies and creates reach 15
  • VelocityRapid insights provide competitive advantage 16
  • VarietyEveryone’s an advertiser, broadcaster and data generator People with people People with Machines 17 Machines with Machines
  • The Connected Customer 18
  • Channels most commonly used 19 Eloqua and CMO.com B2B Benchmark Study Q4 2012
  • Quick Poll 20
  • Measuring the basics37% do not track the revenue (closedbusiness) generated by campaigns.29% do not measure sourced-opportunities generated by campaigns.20% do not measure the number of new 21sales leads generated by marketingcampaigns. Source: Pardot
  • It’s still a challenge“The top challenge for marketersremains to better quantify andmeasure the value of marketingprograms, in spite of improvementsin accountability over previousyears.”- CMO Council 22
  • It’s about credibility“Seventy-six percent (76%) of B2Bmarketing professionals agree orstrongly agree that their ability totrack marketing ROI gives marketingmore respect.”Source: Forrester Research 23
  • The Data Challenge 24
  • 25Signal or Noise?
  • Information or Insight ? 26
  • Tracking the digital footprint 27
  • 28Campaign Timing
  • 29
  • Different Data. Different Databases. 30
  • 31
  • Key steps to high-performancedemand generation 32
  • Key steps to data-driven demand gen1. Understand what you want to achieve2. Create a solid data foundation3. Track critical touch-points in the customer life-cycle4. Integrate your systems5. Test and learn6. Visualize and communicate results 33
  • Understand whatyou need to achieve 34
  • Focus on what matters1. Think like a CEO/CFO2. Speak the language of business3. Align marketing objectives with business objectives4. Connect marketing activities and investments with business outcomes5. Define What to measure 35 When to measure How to measure
  • Plan for Measurement1. What business outcomes are you trying to impact?2. How much do you expect this program/activity to contribute?3. How will you know that this program achieved the objective(s)?4. What metrics would you expect to see?5. When would you know to change course?6. What data will help you understand our current state?7. What data and metrics will communicate the program’s effectiveness and value? 36
  • 5 questions to guide your measurement insight1. What are your specific objectives for marketing investment and how will you connect your investments to incremental revenue and profit?2. What impact would a 10% change in your marketing budget (up or down) have on your profits and margins over the next year? The next three years? Five?3. Compared to relevant benchmarks (historical, competitive, marketplace), how effective are you at converting marketing investment into revenue and profit growth?4. Which are appropriate targets for improving revenue leverage (defined as dollars of profit over dollars of marketing and sales spend) over the next few years? Which initiatives will get you there?5. What questions do you still need to answer with regard to your 37 knowledge of the return on marketing investments? What are you going to do to answer them? Source: MarketingNPV
  • Primary Marketing Metrics aligned to Business Goals1. Revenue Net new deals2. Profit Customer expansion3. Market Share4. Margin Marketing Effectiveness and Efficiency5. Leads sourced or influenced by marketing 38 MQLs and SALs Opportunities
  • Secondary Marketing Program Metrics1. Registrations, Conversions or Inquiries2. Lead Quality by Lead Score3. Spend (Cost per Conversion, Cost per Qualified Lead)4. Engagement CTRs Attention ( Time on site, Interact with Content) PR and Social Comments, Tweets, Likes, Shares 395. Etc.
  • The Time Dimension 40 Source: Lenskold Group
  • Measurement Don’ts1. Use Vanity metrics2. Measure what is easy3. Focus on quantity over quality4. Focus on activity, not results5. Efficiency instead of effectiveness 41 Source: Marketo - Definitive Guide to Marketing Metrics and Analytics
  • 42
  • Create a solid datafoundation 43
  • Reliable data leads to better decisions1. Data Governance Data quality ■Is it current? ■Is it correct? ■Is it consistent? Completeness Compliance 44
  • Treat data as a portfolio1. Data Governance Data quality ■Is it current? ■Is it correct? ■Is it consistent? Completeness Compliance 45 Source: Marketo
  • Determine Your Data Profile1. Prospect/Customer Profile  Contact Information  Company Information  Ideal Customer attributes – revenue size, industry2. Prospect/Customer Engagement  Website Visits  Email Opens, Clicks, Forwards  Blog Comments  Social activity3. Lead Type Categorization  Source/Channel/Industry/Job Role 46
  • Prioritize and tracktouch-points 47
  • 48
  • 49Source: Forrester
  • Lead management workflow 50
  • Categorize your Marketing Channels1. Purchased Lists2. Web3. Social4. Partner/Reseller Channel5. Event6. Etc. 51
  • Setup and manage your tracking codesElement # Characters Example 1. Funnel 3 OSA a. Outside Sales Funnel A OSA b. Outside Sales Funnel B OSB c. Outside Sales Funnel C OSC d. Marketing Funnel D MKD 2. Quarter 3 (408) 3. Campaign Type 4 EMRL a. Email i. Rented List EMRL ii. House List EMHL iii. Internal List EMIL iv. Brand List EMBL Registered Users Free Trial ( Vscape Lite Users) b. Webinar WEBS c. Banner Ads BNAD d. Online Third Party ONTP e. Conference / Tradeshow CONF f. Website VFMW h. PPC Example: g. Public Relations PBRL PPCS i. Social WB20 j. List Development LDEV 4. Vertical / Market Focus ( HO) 2 Characters a. Industry A b. Industry B Source code = MKD113EMBLIAB2BWebinarData-Driven070313DE IA IB c. DISTRIBUTION PARTNER DP d. OTHER OTHR e. MEDIA MD 5. Vendor Variable 6. Offer Variable 7. Drop / Start Date 6 Mmddyy 8. Campaign Element (if multiple types of 2 NA promotion, then the specific type for this source code, else use code “00”) a. Not applicable or None 00 b. Dedicated Email DE c. E-newsletter sponsorship ES d. Banner / Text Ads e. Whitepaper/ Offer Listing BA LI 52 f. Company Listing / MicroSite CL g. Other OT h. Fax FX
  • A note about attributions 53
  • Insert your tracking codes 54
  • Integrate yoursystems 55
  • Identify your systems 56 Source: Chiefmartec
  • Understand your technical infrastructure 57
  • Get the systems talking to each otherWeb CMS, market automation and CRM offer a common view ofthe customer that drives personalization across web and email 58
  • Test and learn 59
  • Test, review, optimize 60
  • Visualize your data 61
  • Tell a story 62 Source: Lenskold Group
  • What’s the MROI? 63 Source: Eloqua
  • Visualize your impact 64 Source: Eloqua
  • It doesn’t have to be pretty! Q4 2012 65
  • Questions? 66
  • Contact UsShawn De Souzashawn.desouza@edynamic.netTwitter: @shawndesouzawww.edynamic.net 67
  • Thank You 68