Skip navigation
All Places > Champion Program > Blog > 2016 > May

As a regular contributor to the community, here are some advice I would give to beginners who want to maximize the chances to get some help from the community:


1-Choose the right place to post

Post your products questions to the place where you have the greatest chance to get a quick answer. This is set at the bottom of the discussion entry screen:

  1. "Products" is the best place for anything related to the use of the products (MLM, RTP, ...). Most of the time, this is THE place to start. Most of the community members start to look there when they have some time to answer questions. Furthermore, questions and discussions in this place resurface each time someone comments them, making them more visible
  2. "Community help and feedback" is the best place for anything related to how this community works
  3. "Champions: the Marketo elite" is not that a good pick, unlike what one would think: only a small subset of the users are monitoring this place. the questions there do not show on the pending question lists and you are quite less likely to get a quick answer. My experience is that questions posted there receive far less answers.
    [EDIT]: based on Liz' comment below, "Champions: The Marketo Elite is for people to find out more information about the Champion program." And if you did post it to the wrong place, you can ask Elizabeth Oseguera or Scott Wilder to have it relocated.


2-Choose the right type of post

The choice of the type of post will impact the quality of the answers you will get as well as the timeliness of these answers:

  1. Questions: In order to post a question, you have to create a "Discussion" (weird, isn't it? ).  "Discussions" are for any questions and information and by default, a "Discussion" will in fact be a "Question". As a contributor, like all other community contributors, I know that questions are from people who need real help, most of the time quickly. Start there, unless you really know your post belongs to somewhere else.
  2. Discussions: You can also transform a question in a simple information to the community, un-clicking the "Question" checkbox. This will make your post a simple information for the community. Always very appreciated from everyone . But then, do not necessarily expect an answer, you are more likely to get "thank you's" here.
  3. Ideas: Create and Idea only if you are sure it is a missing feature. If you are not sure, start with a question. If you are pointing out a missing feature, the community will often answer something such as "That a nice idea, post it, we will vote". Do not post questions here, it will not help you as you should not expect a "how to" answer. On the other hand, accept that idea relevance can be discussed by other community members. And always search before posting ideas. Idea duplication is very frequent and it dilutes votes, which makes them less likely to attract PM attention.


3-Focus on question length and clarity

The way you will right your question will condition whether or not you will get an answer:

  1. Ask only 1 question per post: the longer and the more complex a question seems at first glance, and the less likely it is to get an answer quickly. Really! We (other community members) browse questions and if we get only 5 minutes ahead of us, we will focus on short and clearly expressed questions that we can answer in this short amount of time. Also, on this side, avoid asking a question as a answer to your or someone else's question if it is not directly related to the primary question. Doing this, you are again limiting your capacity to get a quick and rich answer, as most people will not see your question.
  2. Do not ask a new question in the answer thread of another post. This most of the time will be ignored by contributors because it has no visibility at all (only people who have already contributed to the thread will see it).
  3. Add screenshots and code samples. Do not hesitate to add some screen copies of the smart lists, flows, scheduling tab, admin sections you need help on (anonymize them if needed). If you need some help on an HTML template, post the code. Same for API usage.
  4. Do not ask the same question in multiple posts. It will scatter the answers at best, having various contributors answering multiple times on distinct aspects of the question in different places. At the end of the day, you will spend more time reconciling the answers and these answers will be of a lower quality because the contributors will not have the whole picture. It will also give people who answer the impression they become crazy, wondering whether they have dreamt answering it or not . If you have entered the question twice inadvertently (it happens) delete one of them rapidly.
  5. Use ideas as clues for something missing:  If you have the feeling something is not working as you would expect it from the product, search the "ideas" section. Very often someone has had the same need and entered an idea, indicating the need for an improvement. It will tell you that you are right. And then vote and look at the discussion in the idea if any workaround has been posted by a contributor.


4-Reward answers and responders

  1. Rewards the answers. Community members spend graciously some time trying to help and appreciate to be recognized for this. And believe me they also have a job aside from this. So, do not take it for granted, hit the "helpful" and "like" buttons as often as you want, and do it even if you did not write the question in the first place.
  2. Mark them as answered when you are done. This is done clicking the "correct answer" button on one of the answers and give the signal to other community members that you are OK and that they should concentrate on other pending questions. Also remember this is a way to reward the person who helped you, so hit wisely and do not reward yourself
  3. Vote for ideas when you find them relevant. It is not a waste of time, even if the number of open ideas is much larger than the number of done ones



I've attended Summit for 3 years as an attendee, but for the past 2 years did it as an exhibitor. Given that many Marketo marketers may have tradeshows in their arsenal of marketing channels, I figured I'd give you a bit of a behind the scenes view of the Marketo Summit from the exhibitor perspective in hope to help you at your next tradeshow.


I can easily say this is our biggest marketing investment for the year. Almost everything we do is digital advertising, but I believe at some points you need to cross channels and there is no better avenue than the Marketo Summit to reach our customers. Unlike some other companies, we ONLY sell to Marketo customers, and pretty much everyone who uses Marketo could be our customer, so you don't find a better concentration of potential customers than at Summit.


What we did:

  • Expo hall booth
  • Ice bar party
  • Videos (customer testimonials, what's new and party)
  • Who's Who Infographic


Exhibitor Booth


There are many packages available to exhibit on the show floor. They vary drastically in price. For us, we're a small growing company so spending hundreds of thousands of dollars on a booth is out of the question - but many companies do. We went with the exhibitor booth, which set us back about $10K. The booth is a high financial investment for us, but low time investment (other than being at the booth). Marketo does a great job of taking care of most of the booth logistics, so its really a breeze. We produced a video that would run on the screen at our booth showing real-time numbers from what's happening in our app, but that was probably the biggest time investment we made.


We had a ton of great traffic at our booth, and lots of really good conversations. At the end of the week we had about 60 scans at the booth, although I can definitely say our team did not scan every single person we had a conversation with. This bit is really quality over quantity, but when you look at the cost-per-lead it is definitely pretty high ($166/lead). Personally, I believe that although in Marketing we should strive to measure and report on everything, there are some intangibles of having a booth with regards to branding that may never be able to be reported on.


Ice Bar Party


Jeff RevEngine from RevEngine Marketing is a very good partner of ours, and he reached out asking about doing an ice bar party with him. Given we are in Canada, ice is right up our alley and we jumped at the opportunity. What I liked about our party was that it was not really competing with anything at the time we had it at, in fact there was really nothing going on before the Hakkasan party other than dinners. Also, the ice part of it makes it a bit unique and more of an experience than just going to a bar. Finally, it was at the Mandalay Bay, so not sure about you guys but I feel like I needed to get out of the MGM at that point or I was going to lose it.


The party was definitely a big time investment. We made a new email and new landing page template for the show, and handled setting up the program in Marketo. Although Knak makes the process of making emails and landing pages easy, first we have to design and develop the actual template that our customers download from Knak, which is what ends up taking the most time. For the landing page in particular we did a lot of stuff that hasn't been done before (countdown timers, pop-up forms, video backgrounds) so it was time consuming to say the least. Jeff was great at taking care of the logistics of the bar and what not, and our other two partners LeadSpace and Rybbon were really great to work with as well. Having good partners is key - and we had some of the best.


Another challenge was figuring out how many people we needed to get registered and how many would show up. Our venue had a capacity of 300-350 so we knew that was our ceiling. We also figured we would have about a 40-50% attendance rate, so we were initially aiming to get around 200-300 people registered. We ended up getting almost 800 people to register and had just under 300 attend. The entire party cost us less than $20K, so split 4 ways it really was not too bad. Given some other sponsors spent way more than that on their parties, I felt as though we got a really good ROI and more importantly, everyone we talked to had an awesome time.


This is the first year we've experimented with videos. We got a really good recommendation from a client of ours, Brendan Farnand, who knew an excellent videographer. This definitely makes a big difference working with the right people who have the right equipment and demeanor to get what you need. Shooting videos is still a ton of work though. We lined up some key interviews with customers and be prepared to invest quite a bit of time into scheduling and approvals and all that fun stuff. In the end we totally believe they will be worth it.


Screen Shot 2016-05-17 at 8.39.34 AM.png


Who's Who Infographic
This is the second year that we've done this infographic, and it consistently is a good draw. We basically take all of the partners that go to Summit and bucket them into different categories to help attendees better understand where all the vendors fit. We find it generates some hype pre-show and is just a useful piece of content for marketers to consume before the show.


The Results?


It's too early to tell, but we met a ton of potential new fans, met some familiar ones, made some awesome relationships and had a really good time doing it. Now, its up to our product team to deliver on the experience that we are promising from Knak and go from there!

It's hard to believe Summit is over! My brain is still trying to process everything that it absorbed (especially everything about ABM), and hey – if I ever recover from the cold-med-induced haze I've been living in for the past 3 days, I think I'll have some actionable takeaways for my team!


If your situation is anything like mine, you'll spend your coffee time on Monday morning trying to corral all your feverish notes into some kind of coherent narrative that justifies the trip. What best practices can you implement now? What improvements can be made with the help of a vendor partner? What can you do in the next quarter to improve process, and in the next year to prove ROI?


Those are some fun questions to answer, and doing it well always makes it easier to justify the trip next year... Obviously so there can be more learning, and, um... shenanigans. Sooooo... To help in that endeavor, I wanted to share my session materials again here in the community. If you attended my session, thank you so much. If you missed it– hey, I get it, there were so many fantastic sessions to choose from... But I don't want you to miss out on this either!


I had a blast teaching you guys how we approach the engagement engine at STANLEY, and even moreso in creating/recording all the materials. So without further adieu, use the below materials to rev up your engagement engine and make some dramatic process improvements that will help you prove ROI through your content marketing, enforce consistency and compliance across your team, and save you a metric boat-load of time.


I look forward to seeing each and every one of you next year at Summit, and hope I can give something like this back to the community again soon!




18-page Step-by-Step Guide


Like I said in my session, when you play the Game of Clones, you win or you die. But fear not! With this guide, you'll bask in the sweet luminous glory of R'hllor's light and, um... not die. In these pages, I delved into excruciating depth so that any member of your team, regardless of their level of Marketo-fu, can follow the steps and deliver flawless content programs in your instance that provide scalability for the future!


Let the Force Flow Through You


A Primer on Tokens (video)



The Full Game of Clones Demo Experience! (video)


View the Session Recording here!

The term “data-driven marketer” is rapidly becoming a redundancy: to be a marketer these days is to be data-driven, whether you work in demand gen, marketing ops, content, or social.


And yet, being an evidence-based marketer is not without challenges.


  • Data - We are simultaneously drowning in data while also missing some critical pieces of it.
  • Time - Marketers still have programs to run and don’t have all day to spend looking at reports.
  • Skills - Data analysis is a skill. Not all marketers have developed it. And that can lead to very bad decisions (a little analysis is a dangerous thing).


Predictive analytics software is so appealing precisely because it solves all these problems. Predictive tools tools tap into our existing datasets, combine them with thousands of external signals, and use advanced statistical methods and machine learning to produce statistically valid insights in very little time.


If we are serious about being data-driven, it’s only logical that more and more of our marketing decision-making will become powered by this sort of technology. What will this future look like?


With this question in mind, I spoke to six predictive analytics vendors about how predictive can be applied to empower marketing. I distilled their feedback into five top use cases for integrating predictive into marketing automation that are all possible today.


How Predictive Analytics Tools Work


Before we explore these use cases, let’s consider how exactly predictive tools work and how they should fit into your existing technology stack.


There are many predictive marketing vendors, each with their own unique features, but at a high level they all do the following:


  • Read Internal Data - Evaluate the demographic/firmographic data in your CRM, behavioural data in your MAP, or potentially even information from a product database or internal data warehouse.
  • Add External Signals - Enrich those records with external data points on your contacts and accounts (e.g., technologies used, job posting activity, intent data, and so on); most vendors have their own web scrapers to collect this information and also purchase it from third-party data vendors.
  • Build a Model - Evaluate your historical success metrics and use analytical techniques to build a predictive model. This model identifies variables in your data that correlate with successful outcomes, and it can now be applied in various ways to make data-driven marketing decisions.




How Predictive Marketing Fits into your MarTech Stack


So how does a predictive tool fit in with your existing marketing automation platform? The key thing is to understand the roles of each system in your stack.


The System of Execution


Automation tools like Marketo excel at enabling marketing execution. Marketo is a workflow machine, allowing you to define rules-based actions with enormous flexibility and complexity.


Marketing automation also tends to be the central integration point for all marketing activities - the hub of the wheel that drives outreach across multiple channels through more specialized integrated apps. You can apply that incredible workflow power to achieve outcomes directly or through a variety of integrated systems.


For all these reasons, it makes sense to think about marketing automation as your primary “System of Execution”.


The System of Insight


While marketing automation gives you the tools to act, they don’t necessarily tell you what you should do. That’s where predictive comes in. A predictive tool can ingest all your data, combine with external signals, and provide decision support and guidance. As Jim Walker (VP of Marketing at EverString) put it to me, this is your “System of Insight”.


From this perspective, predictive analytics can be the “brain” that powers the execution of your sales and marketing programs via your MAP, CRM, and through a stack of specialized execution tools.



(Side note: there are clearly some areas where Marketo is both system of execution and insight -- e.g., RTP provides predictive content recommendations already. And Marketo is investing heavily in building up its own predictive capabilities, so we may see more convergence between execution and insight going forward.)


Now that we’ve got some context, let’s look at how this interaction between insights and execution can work in practice with some concrete examples.


How to Combine Predictive Insights with Marketing Automation


Lead Scoring


This is the most well-known marketing application of predictive analytics, as most vendors started out as predictive lead scoring tools before expanding to other applications.


Predictive lead scoring is a lot like the traditional lead scoring that we build in Marketo, only smarter. Instead of using anecdotal insights or limited data analysis to decide that a job title containing “CMO” should be +30 points and someone attending your webinar should be +15 points, you feed all your data into your predictive model and let the algorithms determine how leads should be scored.


Don’t get me wrong: traditional lead scoring can still be tremendously valuable in prioritizing your leads. But there are limits to how far you can take it, even if you are a data geek and spend a lot of time working in a spreadsheet. A computer can consider thousands of variables and the correlations between them to deliver a lot more predictive power.


Calculating a predictive score for a lead is just one part of the puzzle. Many tools can also help enable salespeople to act on the data. For example, Nipul Chokshi, Head of Product Marketing at Lattice, stresses the importance of making it easy for sales to take action on the highest-scoring leads. He suggests to accompany the predictive score with insightful context, such as the external signals that drove the score. For example, you could tell a rep that the prospect account uses complementary technologies or that contacts at the company have been demonstrating intent, and so on.


He notes it’s also important to make the predictive data actionable - for example by providing call plans with talking points and discovery questions all in one easy-to-access place.


These steps ensure marketing is building real alignment by providing full context behind the score and actionable insights for next steps.


Demand Generation/Account Targeting


Lead scoring is fundamentally an inbound application of predictive analytics. Demand generation turns this on its head, allowing you to go outbound and support an account-based marketing strategy.


Instead of telling you which of the leads already in your funnel are the good ones, predictive demand generation tells you which accounts should be in your funnel and then gives you the information for contacts on those accounts.


Account selection is sometimes called “look-alike” modelling, because the tool will take the profile of what a good customer looks like for your business (How many employees? Annual revenues? What technologies used? etc.) and then match that profile against a proprietary database of companies. Every vendor I spoke to has one, and they typically have millions of accounts.


You can then import these new contacts directly into your CRM and MAP and from there engage them in outbound sales and marketing programs.




Nurturing is all about cultivating relationships with the right people until they are ready to buy. But how do we know how ready they are? Using predictive analytics there is a variety of ways to more intelligently route leads into the correct nurture.


Architecting Your Nurture Around Fit


Sean Zinsmeister, Senior Director of Product Marketing at Infer, shared some of his approaches for architecting a lead nurture using predictive analytics with me. In Sean’s diagram below, leads are routed based on likelihood to convert (fit data) so the messaging sequence can be calibrated accordingly. “A” leads are routed directly to sales while other leads are given increasingly softer messaging the less likely they are to be sales-ready.




Architecting Your Nurture Around Buying Stage


When it comes to nurturing, Amanda Kahlow, CEO of 6Sense notes that “a key factor missing in this is timing: whether the prospect is even in an active buying cycle to care about your products and services.”


According to Kahlow, the key to resolving this is better activity data that allows marketers to connect the behavioural signals collected on their own website with “buyer intent signals from third-party activity data across the B2B web.”


For example, she notes that if multiple employees from Acme Inc. are clicking on ads for server virtualization technologies, browsing content related to virtualization on major publisher sites and buying guide portals, or downloading related resources across the B2B web, Acme Inc. might be considering a purchase in this area.


“This intent data from Acme’s buying committee is aggregated at the account level and fed into our predictive engine, where it can be used to determine not just whether Acme is in-market for server virtualization, but even the specific buying stage they are in.”


I think this intent data has powerful implications for your nurturing. For example, if you were equipped with detailed buying stage insights about your prospects, you would no longer need to start everyone on an early-stage or “awareness” nurturing track just because they are new to your database. If you have intent data to suggest they are actually well-along into research or even consideration of your specific product, you can route them accordingly and give them the most relevant content.




A marketing rule of thumb is that the more relevant your content is to a prospect, the greater impact it will have.


One big challenge to relevant marketing is a lack of knowledge about your prospect and their interests. Are they after product A or product B? Which of 5 different pain points/value propositions should you emphasize? Should you talk about integrations with complimentary products they are already using? Many predictive tools can help you solve these problems.


Nipul Chokshi suggests creating multiple scoring models for different products. This way you can evaluate which product has the highest score and provide the lead with content they’re most likely to be interested in.


Other vendors expose rich demographic/firmographic/technographic data about your prospects and allow you to build marketing campaigns around those data points. I’ve seen Leadspace at work during a client engagement and was impressed with how it provides full-scale data enrichment in addition to building predictive models on top of that data.


As an example of what this enables, you can detect if a prospect is using a complementary technology and then personalize emails and landing pages to highlight your compatibility with that technology or have a completely different series of touchpoints based on this knowledge. It also allows you to potentially cover both data enrichment and predictive needs with a single app.


Lastly, it is also possible for a predictive tool to do the heavy lifting in building rich profiles for segmentation - profiles that go far beyond just a handful of data points. Infer has a really interesting tool for this purpose, which they call their Profile Management solution. It aids users in combining many data signals together to form what Zinsmeister calls a “hyper-segment”, a profile of one of your ideal customers. Infer will use its predictive model to assess how desirable the segment is in real time and gauge the business impact all the way through opportunity win-rate.


Now you can work to develop highly relevant content that is completely designed around the needs of that profile. And as you identify or acquire new contacts that fit this desirable profile, you can feed them the extremely targeted messaging that resonates with pain points you know they have.


Marketing Program Evaluation


Jessica Cross, Director, Demand Acceleration and Customer Marketing at EverString, had some great tips on using predictive analytics to evaluate your marketing programs. By evaluating the quality of leads each program produces in real time, you can get a leading indicator about where to invest your marketing dollars. Without predictive, two programs producing the same volume of leads might seem equally appealing, but with the lens of a predictive model you could see immediately that one program is producing leads of much higher quality and should be prioritized.


Predictive Campaigns


During his keynote at Marketo’s Summit in 2015, CEO Phil Fernandez presented the metaphor of the self-driving car as a vision for the future of marketing. In this vision, the marketer will input the goal, and the technology will figure out how to get leads to that destination.


This vision would seem to be a logical conclusion to the development of predictive analytics. But does this mean that the marketer’s creative inputs will soon be obsolete? Far from it, for the marketer still needs to create the destinations on the journey (by designing relevant content and touchpoints), while predictive tools provide the capacity for determining the best route for each customer to take.


Mintigo’s new Predictive Campaigns functionality is designed to do exactly that. Predictive Campaigns can evaluate the relationships between marketing programs, contact and account profiles (defined by technographic and intent data), and successful outcomes to develop predictive models for campaign orchestration.


These models would provide the ability to determine, for any particular person, that they should receive the following touches in the following order through the following marketing tactics to have the best chance of reaching a successful outcome. In other words, this helps marketers offer the right message through the right channel to the right person at the right time – essentially 1-to-1 personalized marketing that’s dynamic to each individual buyer’s journey.


It should be said that it is still early days for this capability and the feature is only available for Eloqua right now , but nonetheless it is a powerful example of where these technologies are headed. And hopefully they will roll out a Marketo version soon.


Lessons Learned


What struck me most when chatting with all these smart and passionate vendors was the extent to which the market is converging in terms of core functionality. All the tools work in more or less the same way and have a shared set of basic applications. The ability to build a predictive model in itself is rapidly becoming commoditized.


Where vendors are differentiating is around the use of that data for enabling sales and marketing to make better decisions. We are beginning to see some new and novel applications emerging, and this is where I would expect to see the most innovation in the months and years ahead. The practice of leveraging predictive data in the system of execution (marketing automation) is still in its early days - I believe the applications above only scratch the surface. This is exciting, because there’s lots of room to grow.


Share Your Use Cases


If you have figured out some advanced ways of using predictive analytics in your marketing automation or sales enablement efforts, I’d love to hear about it! Please share in the comments.




I’m grateful to the following people for spending some time to help inform this post.


Amanda Kahlow, CEO at 6Sense

Jessica Cross, Director, Demand Acceleration and Customer Marketing, and Jim Walker, VP of Marketing at EverString

Sean Zinsmeister, Senior Director of Product Marketing at Infer

Nipul Chokshi, Head of Product Marketing at Lattice

Kylee Hall, Senior Director of Marketing at Leadspace

Tony Yang, VP of Marketing at Mintigo


Disclosure: I work for Perkuto and EverString is a partner of ours.

Filter Blog

By date: By tag: