Failing Ahead – What We Discovered at Cisco from a “Failed” Digital Orchestration Pilot

The trendy buyer expertise is fraught with friction:

You communicate to a buyer consultant, they usually inform you one factor.

You log into your digital account and see one other.

You obtain an e mail from the identical firm that tells an fully completely different story.

At Cisco, we’ve got been working to establish these friction factors and evaluating how we will orchestrate a extra seamless expertise—reworking the shopper, accomplice, and vendor expertise to be prescriptive, useful – and, most significantly, easy. This isn’t a straightforward process when working within the complexity of environments, applied sciences, and consumer areas that Cisco does enterprise in, however it isn’t insurmountable.

We simply closed out a year-long pilot of an industry-leading orchestration vendor, and by all measures – it failed. In The Lean Startup Eric Ries writes, “in the event you can not fail, you can not be taught.” I totally subscribe to this attitude. If you’re not keen to experiment, to strive, to fail, and to guage your learnings, you solely repeat what you recognize. You don’t develop. You don’t innovate. It is advisable to be keen to dare to fail, and in the event you do, to attempt to fail ahead.

So, whereas we didn’t renew the contract, we did proceed down our orchestration journey geared up with a 12 months’s value of learnings and newly refined route on easy methods to deal with our initiatives.

Our Digital Orchestration Objectives

We began our pilot with 4 key orchestration use instances:

1. Seamlessly join prescriptive actions throughout channels to our sellers, companions, and clients.
2. Pause and resume a digital e mail journey based mostly on triggers from different channels.
3. Join analytics throughout the multichannel buyer journey.
4. Simply combine information science to department and personalize the shopper journey.

Let’s dive a bit deeper into every. We’ll have a look at the use case, the challenges we encountered, and the steps ahead we’re taking.

Use Case #1: Seamlessly join prescriptive actions throughout channels to our sellers, companions, and clients.

In the present day we course of and ship business-defined prescriptive actions to our buyer success representatives and companions when we’ve got digitally recognized adoption limitations in our buyer’s deployment and utilization of our SaaS merchandise.

In our legacy state, we have been executing a collection of complicated SQL queries in Salesforce Advertising Cloud’s Automation Studio to affix a number of information units and output the precise actions a buyer wants. Then, utilizing Advertising Cloud Join, we wrote the output to the process object in Salesforce CRM to generate actions in a buyer success agent’s queue. After this motion is written to the duty object, we picked up the log in Snowflake, utilized extra filtering logic and wrote actions to our Cisco accomplice portal – Lifecycle Benefit, which is hosted on AWS.

There are a number of key points with this workflow:

• Salesforce Advertising Cloud shouldn’t be meant for use as an ETL platform; we have been already encountering outing points.
• The accomplice actions have been depending on the vendor processing, so it launched complexity if we ever needed to pause one workflow whereas sustaining the opposite.
• The event course of was complicated, and it was tough to introduce new really useful actions or to layer on extra channels.
• There was no suggestions loop between channels, so it was not attainable for a buyer success consultant to see if a accomplice had taken motion or not, and vice versa.

Thus, we introduced in an orchestration platform – a spot the place we will join a number of information sources by way of APIs, centralize processing logic, and write the output to activation channels. Fairly shortly in our implementation, although, we encountered challenges with the orchestration platform.

The Challenges

• The complexity of the joins in our queries couldn’t be supported by the orchestration platform, so we needed to preprocess the actions earlier than they entered the platform after which they could possibly be routed to their respective activation channels. This was our first pivot. In our technical evaluation of the platform, the seller assured us that our queries could possibly be supported within the platform, however in precise observe, that proved woefully inaccurate. So, we migrated probably the most complicated processing to Google Cloud Platform (GCP) and solely left easy logic within the orchestration platform to establish which motion a buyer required and write that to the right activation channel.
• The person interface abstracted components of the code creating dependencies on an exterior vendor. We spent appreciable time attempting to decipher what went flawed through trial and error with out entry to correct logs.
• The connectors have been extremely particular and required vendor assist to setup, modify, and troubleshoot.

Our Subsequent Step Ahead

These three challenges compelled us to assume in a different way. Our purpose was to centralize processing logic and hook up with information sources in addition to activation channels. We have been already leveraging GCP for preprocessing, so we migrated the rest of the queries to GCP. To be able to remedy for our must handle APIs to allow information consumption and channel activation, we turned to Mulesoft. The mix of GCP and Mulesoft helped us obtain our first orchestration purpose whereas giving us full visibility to the end-to-end course of for implementation and assist.

Use Case #2:  Pause and resume a digital e mail journey based mostly on triggers from different channels.

We targeted on making an attempt to pause an e mail journey in a Advertising Automation Platform (Salesforce Advertising Cloud or Eloqua) if a buyer had a mid-to-high severity Technical Help Heart (TAC) Case open for that product.

Once more, we set out to do that utilizing the orchestration platform. On this situation, we would have liked to pause a number of digital journeys from a single set of processing logic within the platform.

The Problem

We did decide that we might ship the pause/resume set off from the orchestration platform, nevertheless it required organising a one-to-one match of journey canvases within the orchestration platform to journeys that we would need to pause within the advertising automation platform. Using the orchestration platform truly launched extra complexity to the workflow than managing ourselves.

Our Subsequent Step Ahead

Once more, we appeared on the recognized problem and the instruments in our toolbox. We decided that if we arrange the processing logic in GCP, we might consider all journeys from a single question and ship the pause set off to all related canvases within the advertising automation platform – a way more scalable construction to assist.

One other strike in opposition to the platform, however one other victory in forcing a brand new mind-set about an issue and discovering an answer we might assist with our present tech stack. We additionally count on the methodology we established to be leveraged for different kinds of decisioning similar to journey prioritization, journey acceleration, or pausing a journey when an adoption barrier is recognized and a really useful motion intervention is initiated.

Use Case #3: Join analytics throughout the multichannel buyer journey.

We execute journeys throughout a number of channels. As an illustration, we might ship a renewal notification e mail collection, present a personalised renewal banner on Cisco.com for customers of that firm with an upcoming renewal, and allow a self-service renewal course of on renew.cisco.com. We accumulate and analyze metrics for every channel, however it’s tough to indicate how a buyer or account interacted with every digital entity throughout their complete expertise.

Orchestration platforms provide analytics views that show Sankey diagrams so journey strategists can visually evaluate how clients have interaction throughout channels to guage drop off factors or notably vital engagements for optimization alternatives.

The Problem

• As we set out to do that, we realized the biggest blocker to unifying this information shouldn’t be actually a problem an orchestration platform innately solves simply by way of executing the campaigns by way of their platform. The most important blocker is that every channel makes use of completely different identifiers for the shopper. E mail journeys use e mail handle, internet personalization makes use of cookies related at an account stage, and the e-commerce expertise makes use of person ID login. The basis of this concern is the dearth of a singular identifier that may be threaded throughout channels.
• Moreover, we found that our analytics and metrics crew had present gaps in attribution reporting for websites behind SSO login, similar to renew.cisco.com.
• Lastly, since many groups at Cisco are driving internet visitors to Cisco.com, we noticed a big inconsistency with how completely different groups have been tagging (and never tagging) their respective internet campaigns. To have the ability to obtain a real view of the shopper journey finish to finish, we would want to undertake a typical language for tagging and monitoring our campaigns throughout enterprise models at Cisco.

Our Subsequent Step Ahead

Our crew started the method to undertake the identical tagging and monitoring hierarchy and system that our advertising group makes use of for his or her campaigns. This can enable our groups to bridge the hole between a buyer’s pre-purchase and post-purchase journeys at Cisco—enabling a extra cohesive buyer expertise.

Subsequent, we would have liked to deal with the info threading. Right here we recognized what mapping tables existed (and the place) to have the ability to map completely different marketing campaign information to a single information hierarchy. For this specific instance for renewals, we would have liked to deal with three completely different information hierarchies:

1. Occasion ID related to a singular bodily location for a buyer who has bought from Cisco
2. Net cookie ID
3. Cisco login ID

With the introduction of constant, cross Cisco-BU monitoring IDs in our Cisco.com internet information, we are going to map a Cisco login ID again to an internet cookie ID to fill in among the internet attribution gaps we see on websites like renew.cisco.com after a person logs in with SSO.

As soon as we had established that stage of information threading, we might develop our personal Sankey diagrams utilizing our present Tableau platform for Buyer Journey Analytics. Moreover, leveraging our present tech stack helps restrict the variety of reporting platforms used to make sure higher metrics consistency and simpler upkeep.

Use Case #4: Simply combine information science to department and personalize the shopper journey.

We needed to discover how we will take the output of a knowledge science mannequin and pivot a journey to offer a extra customized, guided expertise for that buyer. As an illustration, let’s have a look at our buyer’s renewal journey. In the present day, they obtain a four-touchpoint journey reminding them to resume. Clients may also open a chat or have a consultant name or e mail them for extra assist. In the end, the journey is similar for a buyer no matter their chance to resume. We now have, nonetheless, a churn danger mannequin that could possibly be leveraged to change the expertise based mostly on excessive, medium, or low danger of churn.

So, if a buyer with an upcoming renewal had a excessive danger of churn, we might set off a prescriptive motion to escalate to a human for engagement, and we might additionally personalize the e-mail with a extra pressing message for that person. Whereas a buyer with a low danger for churn might have an upsell alternative weaved into their notification or we might route the low-risk clients into advocacy campaigns.

The objectives of this use case have been primarily:

1. Leverage the output of a knowledge science mannequin to personalize the shopper’s expertise
2. Pivot experiences from digital to human escalation based mostly on information triggers.
3. Present context to assist buyer brokers perceive the chance and higher have interaction the shopper to drive the renewal.

The Problem

This was truly a moderately pure match for an orchestration platform. The problem we entered right here was the info refresh timing. We wanted to refresh the renewals information to be processed by the churn danger mannequin and align that with the timing of the triggered e mail journeys. Our renewals information was refreshed at the start of each month, however we maintain our sends till the top of the month to permit our companions a while to evaluate and modify their clients’ information previous to sending. Our orchestration platform would solely course of new, incremental information and overwrite based mostly on a pre-identified major key (this allowed for higher system processing to not simply overwrite all information with each refresh).

To get round this concern, our vendor would create a model new view of the desk previous to our triggered ship so that every one information was newly processed (not simply any new or up to date data). Not solely did this create a vendor dependency for our journeys, nevertheless it additionally launched potential high quality assurance points by requiring a pre-launch replace of our information desk sources for our manufacturing journeys.

Our Subsequent Step Ahead

One query we stored asking ourselves as we struggled to make this use case work with the orchestration platform—have been we overcomplicating issues? The 2 orchestration platform outputs of our attrition mannequin use case have been to:

1. Customise the journey content material for a person relying on their danger of attrition.
2. Create a human touchpoint in our digital renewal journey for these with a excessive attrition danger.

For primary, we might truly obtain that utilizing dynamic content material modules inside SalesForce Advertising Cloud if we merely added a “danger of attrition” area to our renewals information extension and created dynamic content material modules for low, medium, and excessive danger of attrition values. Performed!

For quantity two, doesn’t that sound form of acquainted? It ought to! It’s the identical downside we needed to unravel in our first use case for prescriptive calls to motion. As a result of we already labored to create a brand new structure for scaling our really useful actions throughout a number of channels and audiences, we might work so as to add a department for an “attrition danger” alert to be despatched to our Cisco Renewals Managers and companions based mostly on our information science mannequin. A suggestions loop might even be added to gather information on why a buyer might not select to resume after this human connection is made.

Discovering Success

On the finish of our one-year pilot, we had been compelled to consider the ways to attain our objectives very in a different way. Sure, we had deemed the pilot a failure – however how can we fail ahead? As we encountered every problem, we took a step again and evaluated what we realized and the way we might use that to attain our objectives.

In the end, we discovered new methods to leverage our present methods to not solely obtain our core objectives but additionally allow us to have end-to -end visibility of our code so we will arrange the processing, refreshes, and connections precisely how our enterprise requires.

Now – we’re making use of every of those learnings.  We’re rolling out our core use instances as capabilities in our present structure, constructing an orchestration stock that may be leveraged throughout the corporate – a large step in the direction of success for us and for our clients’ expertise.  The end result was not what we anticipated, however every step of the method helped propel us towards the proper options.

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