The document discusses how to take dynamic content and personalized URLs (PURLs) to the next level for marketing purposes. It describes using recommendation engines and PURLs to provide personalized content destinations that feature relevant offers and resources for prospects based on their interests and behaviors. Specific cases studies are presented of how IBM and 360pi implemented these strategies to increase content consumption and engagement. The key benefits highlighted are that personalized recommendations drive greater lead progression compared to only promoting single offers without context.
Track Owner:
mniedenthal@marketo.com
Deadlines:
March 3rd – 7th – Final dry run of presentations with presenters
March 28th – Final presentation decks submitted
Timing:
50 minutes
10 minutes Q&A
Notes from WebReply:
persistent portal, creating a destination. not a disposable PURL.
- every two weeks
- every once and a while there is something they like
- more impressions
- abstract only, still getting in front of them
- relevance gets something read, resonance gets action
- content matrix and different dimensions
- index to database
- PURLs role is broader than being a vanity attraction
- yes
- testing on millions of emails (comparing left and right)
- read left to right - left is more important than right
- tracking facility
- persistent website, maintenance is easier
- passive tracking, no cookies required
- unlimited flexibility on what is put on a website
- multi-language, messaging. can change the whole freakin’ webpage
- ties prospect to a database directly
- Integration w/ Marketo
-
Notes from WebReply:
persistent portal, creating a destination. not a disposable PURL.
- every two weeks
- every once and a while there is something they like
- more impressions
- abstract only, still getting in front of them
- relevance gets something read, resonance gets action
- content matrix and different dimensions
- index to database
- PURLs role is broader than being a vanity attraction
- yes
- testing on millions of emails (comparing left and right)
- read left to right - left is more important than right
- tracking facility
- persistent website, maintenance is easier
- passive tracking, no cookies required
- unlimited flexibility on what is put on a website
- multi-language, messaging. can change the whole freakin’ webpage
- ties prospect to a database directly
- Integration w/ Marketo
-
* call out the fact that cookies are not necessary
* cross-domain rules cannot extract information from iFrame
* adding URL parameters on the URL string when the person hits the registration button it passes to WebReply servers (takes over submit button), including munchkin code
1. Reg form page
2. When you call form, add URL parameters to form URL, munchkin + system
3. Submit form: WebReply script passes information from regular form fields + URL parameters
4. New contact - store in DB, generate PURL
5. Two munchkin cookies, one from our site, and one from theirs
6. Pass on the scripts to Marketo to do their form submission
7. Refresh to same page
8. Page reloads. Munchkin cookie exists in browser. WebReply tracks Munchkins related to form submission, who submitted?
9. Match munchkin to person in DB.
* Add new person - calls WebReply, sends leadID, grabs rest of information. Assign PURL if they don’t have one, send PURL back ->
* 2 fields: PURL and WebReply contact ID
Key Takeaways:
Personalization increases engagement
Create a destination and they will return
Relevant content is consumed more by prospects
Single call-to-action emails followed by multi call-to-action resource center performs best
This should be the most human-logical choice of a next suggestion as you can create. We find what that should be, and then engineer a solution to fit our business need.
Lead status
* MQL SAL SQL etc
Intro buying stage
SPEED. You need to be one step ahead in queuing these. They’ll see the thank-you page immediately. You have to beat the processing speed of your campaigns to make sure you assign everything faster than they can see it.
SCALABILITY. When my company grows, and my database grows, will this work?
ROBUSTNESS. Will this work tomorrow if I change how I think about things or set things up? Is it minimizing the rework that I will have to do?
WORKFLOW. How much of a pain in the ass am I creating for my team each week? For each new asset that we create?
These are the options, but our recommendation is to do a combination of fields and segmentations, because it meets these parameters on the left.
tweet
Soft stop: = when you want to pause the recommendation because of outside forces, not the recommendation’s fault. Aka when there’s a better fit.
E.g., when your content team comes up with a more fitting piece of content. Or when the prospect shows more advanced interest in buying stage or product interest. Consideration interest and an offer becomes more applicable.
Hard Stop =
Success = When someone downloads the asset,
Failure = when they strike out (show disinterest enough that we choose not to promote the asset again),
Neutral = or if they download the asset before ever seeing your recommendation.
Setting this up so that it sorts automatically, and so the progression statuses can act as measures of your suggested resource success.
Decision-making criteria can change
Buying stages: Awareness (tofu), Research (mofu), Consideration (bofu). TWEET.
REROLL campaign.
Beginning, middle, end
Master striker for processing
Individual strikes when something bad happens:
* Viewed your suggestion three times and chose NOT to download. This is on thank-you pages, confirmation pages, etc.
Three(ish) strikes until we get the picture and stop suggesting that resource.
To maximize the possible uses of the campaign
When another resource becomes a higher-fitness suggestion: when the first-level and second-level reroll logic changes. E.g., they move into Consideration, or show product interest that groups them differently
Neutral end – When the person didn’t actually see your campaign at all, but they downloaded the asset anyway. Changes status to a hard stop.
Successful end – View-based conversion. They saw your suggestion and downloaded either directly by clicking or indirectly by canonical. Changes status to a hard stop.
Soft stops – watches for the suggested resource assignment in lead value to change. Changes status to a soft stop.
Marketo Form w/ Hidden Email Address Field
Marketo Landing Page Template
Marketo Landing Page
Web Server