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

The fashionable buyer expertise is fraught with friction:

You converse to a buyer consultant, they usually let you know one factor.

You log into your digital account and see one other.

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

At Cisco, we’ve got been working to establish these friction factors and evaluating how we are able to orchestrate a extra seamless expertise—reworking the client, accomplice, and vendor expertise to be prescriptive, useful – and, most significantly, easy. This isn’t a straightforward job when working within the complexity of environments, applied sciences, and shopper 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 case you can not fail, you can’t study.” I totally subscribe to this angle. In case you are not keen to experiment, to strive, to fail, and to judge your learnings, you solely repeat what you understand. You don’t develop. You don’t innovate. You should be keen to dare to fail, and in case you do, to attempt to fail ahead.

So, whereas we didn’t renew the contract, we did proceed down our orchestration journey outfitted with a yr’s price of learnings and newly refined route on find out how to sort out our initiatives.

Our Digital Orchestration Objectives

We began our pilot with 4 key orchestration use circumstances:

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

Let’s dive a bit deeper into every. We’ll take 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 prospects.

Right this moment we course of and ship business-defined prescriptive actions to our buyer success representatives and companions when we’ve got digitally recognized adoption obstacles in our buyer’s deployment and utilization of our SaaS merchandise.

In our legacy state, we had been executing a sequence 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 job 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 further 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 isn’t meant for use as an ETL platform; we had been already encountering day out points.
• The accomplice actions had been depending on the vendor processing, so it launched complexity if we ever wished to pause one workflow whereas sustaining the opposite.
• The event course of was complicated, and it was troublesome to introduce new beneficial actions or to layer on further 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 are able to join a number of information sources by means 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 may very well 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 may very well be supported within the platform, however in precise observe, that proved woefully inaccurate. So, we migrated essentially 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 consumer interface abstracted elements of the code creating dependencies on an exterior vendor. We spent appreciable time attempting to decipher what went mistaken through trial and error with out entry to correct logs.
• The connectors had been extremely particular and required vendor help 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 connect with information sources in addition to activation channels. We had been already leveraging GCP for preprocessing, so we migrated the rest of the queries to GCP. In an effort to remedy for our have to 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 help.

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

We centered 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 Middle (TAC) Case open for that product.

Once more, we set out to do that utilizing the orchestration platform. On this state of affairs, we wanted to pause a number of digital journeys from a single set of processing logic within the platform.

The Problem

We did decide that we may ship the pause/resume set off from the orchestration platform, but it surely required establishing a one-to-one match of journey canvases within the orchestration platform to journeys that we’d wish to pause within the advertising automation platform. Using the orchestration platform really launched extra complexity to the workflow than managing ourselves.

Our Subsequent Step Ahead

Once more, we regarded on the recognized problem and the instruments in our toolbox. We decided that if we arrange the processing logic in GCP, we may 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 help.

One other strike towards the platform, however one other victory in forcing a brand new mind-set about an issue and discovering an answer we may help with our current tech stack. We additionally anticipate the methodology we established to be leveraged for different sorts of decisioning resembling journey prioritization, journey acceleration, or pausing a journey when an adoption barrier is recognized and a beneficial 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 sequence, present a customized 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 troublesome to point out how a buyer or account interacted with every digital entity throughout their whole expertise.

Orchestration platforms supply analytics views that show Sankey diagrams so journey strategists can visually overview how prospects interact throughout channels to judge drop off factors or notably essential engagements for optimization alternatives.

The Problem

• As we set out to do that, we discovered the most important blocker to unifying this information isn’t actually a problem an orchestration platform innately solves simply by means of executing the campaigns by means of their platform. The biggest blocker is that every channel makes use of completely different identifiers for the client. E mail journeys use e mail deal with, internet personalization makes use of cookies related at an account stage, and the e-commerce expertise makes use of consumer ID login. The basis of this concern is the shortage of a novel identifier that may be threaded throughout channels.
• Moreover, we found that our analytics and metrics workforce had current gaps in attribution reporting for websites behind SSO login, resembling 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 had been tagging (and never tagging) their respective internet campaigns. To have the ability to obtain a real view of the client journey finish to finish, we would want to undertake a typical language for tagging and monitoring our campaigns throughout enterprise items at Cisco.

Our Subsequent Step Ahead

Our workforce 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 permit 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 wanted to sort out 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 wanted to sort out three completely different information hierarchies:

1. Social gathering ID related to a novel bodily location for a buyer who has bought from Cisco
2. Internet cookie ID
3. Cisco login ID

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

As soon as we had established that stage of knowledge threading, we may develop our personal Sankey diagrams utilizing our current Tableau platform for Buyer Journey Analytics. Moreover, leveraging our current 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 client journey.

We wished to discover how we are able to take the output of a knowledge science mannequin and pivot a journey to supply a extra personalised, guided expertise for that buyer. As an illustration, let’s take a look at our buyer’s renewal journey. Right this moment, they obtain a four-touchpoint journey reminding them to resume. Prospects can even open a chat or have a consultant name or e mail them for added help. Finally, the journey is identical for a buyer no matter their chance to resume. We have now, nonetheless, a churn threat mannequin that may very well be leveraged to change the expertise primarily based on excessive, medium, or low threat of churn.

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

The targets of this use case had been primarily:

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

The Problem

This was really a moderately pure match for an orchestration platform. The problem we entered right here was the info refresh timing. We would have liked to refresh the renewals information to be processed by the churn threat mannequin and align that with the timing of the triggered e mail journeys. Our renewals information was refreshed initially of each month, however we maintain our sends till the top of the month to permit our companions a while to overview and modify their prospects’ information previous to sending. Our orchestration platform would solely course of new, incremental information and overwrite primarily based 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 each 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, but it surely 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—had been we overcomplicating issues? The 2 orchestration platform outputs of our attrition mannequin use case had been to:

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

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

For quantity two, doesn’t that sound form of acquainted? It ought to! It’s the identical drawback we wished 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 beneficial actions throughout a number of channels and audiences, we may work so as to add a department for an “attrition threat” alert to be despatched to our Cisco Renewals Managers and companions primarily based on our information science mannequin. A suggestions loop may 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 realize our targets very in a different way. Sure, we had deemed the pilot a failure – however how will we fail ahead? As we encountered every problem, we took a step again and evaluated what we discovered and the way we may use that to realize our targets.

Finally, we found out new methods to leverage our current methods to not solely obtain our core targets but additionally allow us to have end-to -end visibility of our code so we are able to 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 circumstances as capabilities in our current structure, constructing an orchestration stock that may be leveraged throughout the corporate – an enormous step in direction of success for us and for our prospects’ expertise.  The end result was not what we anticipated, however every step of the method helped propel us towards the correct options.

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