SalesFUSION Webinars - Taming the flood of digital data
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SalesFUSION Webinars - Taming the flood of digital data
- 1. Analyst Webinar Featuring David Raab Capturing, Tracking & Using Digital Body Language of Leads
- 2. About SalesFUSION Leading SaaS marketing automation solution Focus on Marketing to Sales integration Operating in 11 countries Complete b2b marketing platform Some of the highest client retention and satisfaction in the industry Integrates natively with more CRM systems
- 3. About SalesFUSION Leading SaaS marketing automation solution Focus on Marketing to Sales integration Operating in 11 countries Complete b2b marketing platform Some of the highest client retention and satisfaction in the industry Integrates natively with more CRM systems
- 4. ABOUT THE ANALYST DAVID M. RAAB RAAB ASSOCIATES INC. JANUARY 30, 2013 email: draab@raabassociates.com Web: www.raabassociatesinc.com blog: http://customerexperiencematrix.blogspot.com/ Twitter: @draab
- 5. Discussion points • What is Digital Body Language? • Types of data available • Systems and technology for data capture • How sales can use this information • Analyst discussion • Q&A
- 6. The flow of digital body language Digital Conversation Web interactions Email CTR Capture Track & Analyze initial behavior/touch-points Analyze Nurture ideas Remarketing Nurture Ideas Lead Scoring Score Engage Sales Sales
- 7. The Role of the corporate website in your marketing Destination for majority of campaigns Source of high-value prospect behavior analytics A direct extension of the selling team
- 8. Advanced b2b web analytics “Who’s on my site” vs “How is my site performing” Analytics focused on leads and lead conversion Analytics integrated into the lead gen process Analytics that trigger events and alerts Information is captured and appended to CRM Information is used by sales in addition to marketing/webs team
- 9. What is website visitor tracking The identification and tracking of individuals and companies visiting your website Enabled by placement of a 1st party cookie on the visitor’s pc and relation of their IP address to their email address Tracks the visit detail in the context of lead generation Information gathered includes pages, downloads, time on site, location and much more.. Information gathered is integrated with CRM Information gathered is actionable and drives sales-related processes
- 10. Google Analytics vs website visitor tracking Google Analytics Website visitor tracking Performance of website Places 1st-party cookie Geographic information Tracks a person or company Top pages Identifies companies based on Bounce rate reverse IP append Visit depth Information is used in lead Return visitors scoring/nurture marketing Information used by web team Information is embedded in CRM for site optimization Information drives sales lead alerting via email
- 11. Important metrics to b2b sites Visitor Loyalty - How often do visitors visit the site? Do your visitors visit once a month? 3 times a month? 10 times a month? Compare this metric over a period of time, for example compare this month to last month or this quarter to last quarter. Visitor Recency - How long has it been since a visitor last visited? Again, compare this to two different time periods to see if there is a change or did things remain the same. Depth of Visit - Measures the number of pages viewed by your visitors. Here you will be able to view how many pages visitors view on your site. Always compare metrics over a period of time and try to get an insight into whether visitors are viewing more pages or less.
- 12. Trends in b2b web analytics Information is moving from analytical to actionable – companies want information gathered/presented in ways that can be used in sales funnel advancement Incorporating social metrics – monetizing social media efforts will depend on integrated web analytics and website visitor tracking Integrated approach – Disconnected tools being replaced with integrated solutions that can automatically act on web activity
- 13. Reading the Digital Body Language of Your Prospects David M. Raab Raab Associates Inc. January 30, 2013 email: draab@raabassociates.com Web: www.raabassociatesinc.com blog: http://customerexperiencematrix.blogspot.com/ Twitter: @draab
- 15. O vai to Ua poia oe i'oa anei oe Ia orana Nohea mai oe
- 17. Listening Process • capture online behavior • isolate useful behaviors • capture results • integrate behavior with results • identify correlations • make predictions
- 18. Listening Tips • store attributes in a content repository • store and scan the raw data • content first, then patterns • look for differences by segment • track changes in what’s offered • focus on significant correlations
- 19. Not done yet.
- 20. Language Testing is Different
- 21. Testing Tips • design tests around hypotheses • flag test groups and behaviors directly • limit number and complexity of tests • use true multivariate designs when possible
- 22. Multivariate Design Separate Tests Image image A / headline A 10,000 Test image B / headline A 10,000 Headline image A / headline A 10,000 Test image A / headline B 10,000 total 40,000 Multivariate Test image A / headline A 5,000 image B / headline A 5,000 image A / headline B 5,000 image B / headline B 5,000 total 20,000
- 23. Sample Size Required Response Quantity (95% confidence) Difference to measure Responses per cell 5% (e.g. 1.00% to 1.05%) 2,500 10% 700 15% 350 20% 200 25% 75
- 25. When to Extend • can’t predict today • high value from improvement • can’t use analytics instead
- 26. Three Steps to DBL Literacy • listen carefully • test your understanding • extend the vocabulary
- 27. What Next?
- 29. What are we capturing in b2b web visitor tracking? 1. Known visitors – previously identified by email click/form completion 2. Known companies – identified by reverse IP append 3. Unknown visitors – raw SEO data Email marketers who recognize and act on the changes that have taken place in the ways their customers choose to communicate with them and with each other will be in the best position to adapt their email programs and stay relevant.
- 30. What are we capturing in b2b web visitor tracking? Combination of traditional analytics plus unique visitor demographics and site behavior IP-level detail Geo-location SEO information Email marketers who recognize and act on the changes that have taken place in the ways their customers choose to communicate with them and with each other will be in the best position to adapt theirPage-level detail email programs and stay relevant.
- 31. How do we capture and display this information? 1. Email click through – assuming the email/WVT solution is the same 2. Form completion 3. First-party cookie is placed on PC 4. Related to IP Address and Email Address and CRM GUID (if applicable) • Not 100% • People can clear cookies or browse on a different machine • Good content increases identified individuals • Give people a compelling reason to self-identify
- 32. Data appending for known companies 1. Appends additional company detail to identified organizations 2. Can allow users to search and purchase contacts from data appending solutions – Jigsaw…etc. 3. Purchased users – can be enrolled into campaigns….you may get lucky!
- 33. How do we use the data in a practical way for b2b? Sales reports – companies on the site • Meaningful reports • Delivered via email • Filtered based on role/geo • Make information actionable – click to open in CRM
- 34. How do we use the data in a practical way for b2b? Contact/Account level alerts • Controlled by lead scoring • Managed by lead assignment rules (from CRM?) • Leads on a silver platter for sales • Beware of overkill – throttle the alerts accordingly
- 35. Thank you! Q&A Visit our online resource center PDF Materials & Video will be available White paper – Available 1/31/13 Visit our online resource center Integrated Marketing Automation for… Focused 100% on integrating Marketing and CRM Clients are raving fans of hands-on service Most aggressive pricing in market 30-day Live Trial Pre-integrated to more CRM systems than any other vendors in our space
Notes de l'éditeur
- [IaOrana. Uapoiaaneioe. welcome. are you hungry?]I know you’re all sitting at your desks at work right now, but I want you to imagine you’re sailing in the beautiful South Seas…warm, tropical breezes caress your cheek…a small cloud hovers on the horizon, and as you sail closer, a lush, green jewel of an island rises underneath …finally you drop anchor in the lagoon…friendly islanders paddle out to meet you...…and you can’t understand a word they say.
- That’s the problem you face if you’re Captain Cook visiting Tahiti for the first time in 1769. He knows he’s in a wonderful place and he knows the locals have important things to tell him, but he just doesn’t speak their language. The success of his mission – to observe the transit of Venus – and his very survival depend on him learning it, fast.As marketers today, all of us face that same problem as Cook, except the language we need isn’t Tahitian, it’s the language of online behavior, or digital body language. It’s how our customers increasingly express themselves, especially in those early stages of the relationship when they have no interest in meeting with a live sales person. Like Captain Cook, you can only succeed if you learn to speak the new language yourself.Fortunately for Cook, he had on board Joseph Banks, a wealthy dilettante who had wheedled his way onto the ship as chief naturalist, accompanied by an entourage of assistants, servants, and dogs. Banks proved to be a talented and tireless linguist, providing Cook with the understanding he needed to work with the Tahitians. Today you’ll learn how to be your own Joseph Banks, becoming fluent in in your customers’ digital body language. Like Banks, you’ll have to work hard and build your understanding in stages. Let’s get started.
- Think back to that moment of first contact. Those friendly islanders padding to his ship are saying something like this: welcometoourislandthatplantispoisonhavesomefishwelltradenailsforsexTo you, it sounds like total gibberish, but somewhere in there are little nuggets of meaning – nuggets that are really important, like “that plant is poison” and “do you want fish”. So your first job in learning any new language is listening, so you can first identify and then understand individual words.(Incidentally, the line about nails for sex is a true story, which I’ll let you look up on your own. Suffice it to say that by the time Cook left Polynesia, his sailors had removed so many nails that the ship barely held together.)In terms of digital body language, “listening” means capturing the online behaviors. Your marketing automation system does this by logging search terms, email response, Web page views, form fills, and other activities. Of course, this doesn’t happen automatically: you have to set things up properly by putting scripts on pages, dropping cookies, and storing web logs. The next step is to identify the behaviors you’ve captured. This is the equivalent of recognizing individual words within a stream of speech. In digital body language terms, it’s selecting things like visits to marketing-relevant Web pages. You won’t necessarily know at first which behavior actually matters, so you’ll just have to take a guess, erring on the side of capturing pretty much anything that might be useful. To do the isolation itself, you’ll need parsing or reporting tools, which may or may not be built into your marketing tools. Once you’ve isolated the items, you’ll probably want to classify them into meaningful groups, such “pricing pages” or “feature lists”. You’ll store them in a database where they’re easy to analyze and where they’re time-stamped so you know what happened when.The third step is to capture results. Results are the things you want your digital body language to predict, like someone advancing to a new lead stage or making a purchase. They’ll often come from different systems than the behaviors: for example, lead stages may come from CRM and purchases may come from Accounting. Those systems may or may not have identifiers that tie the results directly to the individuals in your marketing automation system. If not, you’ll need a process to link them.Finally you get to identify correlations between the behaviors and the results. On one level, this is the equivalent of understanding what people mean when they say something. For Banks, it was as simple as watching a Tahitian point at a tree and realizing that ‘uru’ meant ‘breadfruit’. For you, it’s more challenging because you’re not simply doing a translation but are trying to understand how current behaviors can predict future results. So this is where the real analysis comes in. On the other hand, you have a computer and Banks didn’t.
- Here’s a summary of the process from Banks himself:
- Helpful fellow that he is, Banks also has some tips to help with the process:hints: - store content attributes in the content repository, so you don’t have to reapply tags each time you use an item, and so you can add tags after an item is deployed - find tools that can scan the raw data, so you don’t have to decide in advance what you’re about to report on and analyze - start with content (e.g. search terms, pages visited) - move on to patterns (nbr visits during period, sequence of events) - different by segment - be sure to track changes in what was offered/available - be sure to find significant correlations (everybody hits landing page; only a few hit the pricing page)
- Now, Banks was a brilliant observer but he’d be the first to tell you that observation will only go so far. Shortly after the Cook voyage, he was elected president of the Royal Society – a post he held for 41 years – where he was effectively the godfather of experimental science in England. Banks knew that observation can tell you what’s correlated – that is, what things happen together – but it doesn’t prove that one thing caused the other. That takes rigorous testing.If you want to stick with the language analogy, you need to go beyond just listening, and start speaking yourself, so you can then know for sure whether certain words mean what you think they do.
- Of course, testing is happens all the time in marketing, or at least it should. But there’s a difference between your standard marketing tests and the tests for digital body language. Normal marketing tests are designed to change results, or more specifically to improve them. Digital body language tests are designed to improve our understanding, not to improve results. In other words, they’re about making better, more accurate translations. That again goes back to the fundamental purpose of learning to read digital body language, which is to predict what customers and prospects will do.For example, think of an offer test. A traditional offer test would is designed to answer the question: which offer will get more responses. A digital body language offer test would answer the question, which offer will do a better job of giving me the information I want? That information might be, who is a hot prospect, or what are this person’s interests, or what’s their level of purchase intent, or what’s their buying role, or how sophisticated are they, or who knows what. The point is, you’d test different offers depending on your specific goal, and you’d probably measure the results differently too – certainly, you wouldn’t just measure based on response. That said, the basic testing process is the same for language and other tests: - you make different offers to similar groups and track difference in resultsAnd, it has the same basic requirements - you need valid sample size, design w/hypothesis, be able to get clear answerAgain, where it differs is the measurement: - you’re not just looking for higher response or long-term results, but for things like behavior patterns, segment identifiers, or some other type of differentiation - that means need to capture more detailed information than just response / non-response, or even the final outcomes (buy or not buy) - ideally, capture granular detail so can conduct future analysis that wasn’t originally anticipated - probably need to capture intermediate states, since data to determined those may change over time and can’t recreate recognize could be conflict between better results and better prediction; - i.e., particular content/treatment helps identify hot leads but creates fewer ultimate sales; - might think would always take better response, but not necessarily: - would you take 1% fewer sales for 10% lower sales cost?—often, yes, esp. if can redeploy the savings to generate sales some other way
- Hints:- design tests around hypotheses involving multiple changes; more likely to have significant result- directly flag test groups and key behaviors: too dangerous to rely on standard reporting/data, which can be unexpectedly volatile; is check on execution- limit number & complexity of DBL tests: will run short of quantities & will be other, intervening variables- use static MVT when possible, to maximize limited quantities (but only if are confident will be executed correctly)
- Just a little side note here about what makes a true multivariate design - one where multiple variables are tested independently - allows smaller test sizes while still getting valid sample sizee.g. as in example above: need 20,000 not 40,000but still get 10,000 for each itemimpact of non-tested item is cancelled out because each test has sample mix of non-tested items - e.g. both images get 50% headline A and 50% headline Bassumes no interaction among variables, which is usually true - in practice, would retest winning combination to be sure results are accurate- this is simple example; can do many more combinations and need not test every possible combination
- …which brings us to the ever-popular topic of sample sizestatistical details are a little complicated but in most cases, what really matters is the number of responses, not the actual sample sizeso, you work backwards from required responses based on expected response raterequired quantity depends mostly on how small a difference you want to measurein practice, you only test things that will make a big difference, so 25% lift, which requires 75 responses per cell, is reasonablemore important to be sure you’re measuring the right thing – that is, a final result, not an intermediate resulte.g., form fills not open rate; could be get lots of opens but no one fills out the formthese should correlate but experience shows they often don’t
- 3rd stage in translation is introducing new terms to extend native language..keeping with our Tahiti theme, you may not have known that there are no native goats on Tahiti. So when the Europeans introduced them, the Tahitians had to extend their language, which they did by reference to something they did have, pigs, and a distinguishing feature, the goat’s teeth. (examples of English words in Tahitian?) - English tattoo from Tahitian tatau; - other direction: broom -> purumu (no ‘b’ ; also word for ‘road’ because prisioners had to sweep the road as punishment); - translation e.g. fork = spear-food patia-ma’a; goat = pig-tooth pua’a-niho; motorcycle = ‘vehicle-pedal-lightning’ pereo’o-tata’ahi-uira - DBL has similar stage: adding content, flow and analytics specifically to expand what can be captured - add content to clarify intent by making specifically relevant to particular buying stage, user role, or market segment - modify content to offer choices rather than single item, so lead has opportunity to show what’s of interest - track previously untracked behaviors, such as social shares, which give additional data point - use more advanced analytics (e.g. derived measures) to manufacture data - again, isn’t free: - is cost to create new content - more informative content may be less effective at advancing leads (survey vs. item; gated vs. ungated)
- Hints:- because of cost, need to carefully pick and prioritize - where is DBL not working well today (can’t differentiate segment/intent/role/sophistication/stage; data not available from existing sources/patterns) - where would better differentiation would be most valuable (e.g., send to sales, make inactive, reactivate; would be because next action has high cost (sales) or high opportunity cost (won’t contact again – e.g. high unsubscribe rate or bump against contact limits); combination of volume and value per correct answer - use analytics first – is easier than new content, may be more stable (since content and flows always change)…and of course, be sure to test your extensions: goats are bad for the environment
- Here’s Banks one last time, recapping his advice: - listen carefully: observe existing behaviors and correlate with results; start right away- grow your understanding: set up tests to learn more precisely what behaviors mean- expand the vocabulary: present new options and capture more data to gain more information
- so, as you plan your own explorations of digital body language, what should you do next? Here’s what I’d suggest: - build a list of the results it would be most valuable to predict, and make some crude estimate of the financial value - inventory your existing behavior and results data: find out what you are capturing vs. what you could be capturing- identify an immediate opportunity for better prediction: the highest value result for which data is available or easily accessible - execute that opportunity; analyze and learn from the results - build a long term plan by identifying the new data you need for your goals - do this as you’re executing that first project, - define the sequence based on which data gives most value: recognizing one item may support many goals; won’t necessarily add highest value result first, if it takes lots of new data - execute the plan by adding new data and tools - refine your program by testing and expansion - always measure results to keep proving value - first, decide what to look for, based on the value of the information and its availability. Specifically, take a few moments and list - results you’d most like to predict, and behaviors available today - if any of those behaviors can predict any of those results, set a plan to use them, based on the processes we’ve just described - if not, write down behaviors that would predict your desired results, and results that existing behaviors can predict - balancing value of the prediction against availability of the data, pick - if any of those behaviors are already available, set a plan to use them - if none are available, look at what it would take to capture them- - do something immediate, to gain value: analyze, learn, deploy - plan long-term program
- above all, like Cook himself, keep searching. The South Seas have long been mapped and Tahiti itself is a slightly tacky tourist destination, but the frontiers of digital marketing are still unknown, exciting, and filled with unimaginable potential. Thank you and “manuia” (mah-new-yah) (good luck).