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Customer Orchestration and Data Integration   

Customer Engagement

My role

Senior Product Designer

Workshop Facilitator

Conceptual design

service journey

Plan workshops

Conduct interviews​

Scope boundaries

Wireframes

Testing

Case Study Outline

Objective

Solution

Facilitation

Discovery

Research

Design Solution

Iterations

Develop and Deploy

Challenges

Final Outcomes

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Category

SaaS Enterprise

Marketing ​software 

POC

UXTeam

One Product designer

One Visual designer

Rewards Team

Office of the CTO sales team

The Rewards Director

The Customer Success Team

One Project Manager

Engineering Director

 

Real-time data-driven marketing tool

Tibco wanted to showcase its enterprise cloud capabilities to retail marketers by building a cloud application that could leverage AI to automate real-time marketing decisions. 

I was the lead designer from the initial concept to MVP, my role was to find the most impactful way to apply this technology and package the complexity in a way that is simple but powerful to use. 

Through user interviews and workshops, I found that digital marketers need to be able to quickly understand top-performing campaigns, discover insights, and react in real-time and engage with

the right customer, at the right time, in the right place.

 

Good dashboards display data, but a great dashboard is interactive. ... In reality, visual data reporting goes deeper. It not only gives you data, but also lets you interact with it. The ability to interact with the information in front of you helps users understand the data better and enables you to take the best action.

 

Objective

 

Create a Marketing Decision Tool 

The task of this project was to understand the viability of updating a legacy rewards platform and turn it into an autonomous marketing decision tool that could make real-time marketing decisions based on clean data on the fastest network.

 

By identifying user and stakeholder priorities, I iteratively defined and completed designs for the MVP.

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Solution

A delightful enterprise experience.  

This solution offers marketers a concise, unified view of their vast data. It empowers them to autonomously orchestrate customer journeys at scale, providing personalized customer experiences that increase customer satisfaction, loyalty, and value. 

I Included out-of-the-box default, training models and visualization so getting started is easier

 

Examples:

  1. "Most recent purchaser"

  2. “How likely are they to Churn?”

  3. “People who have Churned in the past”

  4. “Their Characteristics and Behavior prior to Churning”

  5. "Targeting those people with some type of experience using their products"

  6. "like recent purchasers"

No-code visual interface

 

Card View audiences

Marketers can autonomously navigate and manipulate their data, and then schedule and publish content directly to social media platforms. Without waiting for the data team.

Card view

Summaries of Audience pool size and what campaigns they are in help to see patterns.

Real-time interactive analytics 

At the point of touch creation of predictive analytic visualizations to deliver at the right time..

Out-of-the-box templates for segmenting audiences  

To speed up the time to market, templates are done programmatically using common filters.

Re-usable playlists for remixing audiences

The reusable playlist concept was aimed at campaign management and content creation. Much like a music playlist, a marketer can remix audiences by combining different attributes and conditions into new collections.

My role

Ownership of an entire service journey

User-centered participatory design

Plan workshops and interviews​

Scoping requirement

Business requirements​

Wireframes

Testing

The team

Sales Executives

PM's

Data Architects

Customer Excellence

Tech Support

Dev Team

Deliverables

Use Cases

Personas

Journey Maps

Business Propositions

Prototypes

Wireframes

Testing Analysis

Consensus

Process

For Whom?_______ Why?________ How?_______What?______

Everything revolves around these questions. I use various investigation and research techniques to derive a holistic perspective about the end-users so I can craft data-informed design decisions based on user feedback and testing.

Research objectives
 

  • What's the MVP?

  • What is the Business proposition? 

  • What are the key market dynamics?

  • The growth potential & strategy

  • Market fit?

  • Challenges and opportunities?

  • Market competition?

  • Global market value & volume 

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Studying the business
 

To reach my objectives I collected

  • Historical data 2014 to 2018

  • Forcast reports to 2025

  • Market reports

  • Forester reports

  • Sales reports

  • Executive reports

  • SWOT analysis

  • Online articles

  • Trends

  • Forums

  • Training videos

  • System diagrams

  • Demos

User Interview Objectives
 

Who is the Marketing Analyst  ​

  • What job is the user  trying to get done?

  • What are the other jobs to be done? 

  • What are her pain points? 

  • How can we relieve the user's pain?

  • What does she want?

  • What are her Goals?

  • What does success look like for them?

  • How do we create value for our customers?

  • What do they wish they could do better? 

  • What is the user journey?

  • What are some user stories?

Study Group

Interviews with
 

  • Customer's Users

  • Internal Marketers

  • Stakeholders 

  • Sales team

  • Engineering

  • Customer Success from the Loyalty Lab.

Her goal is - to generate $50 million, additional profit for her company.

How will she do it? increase retention by 2% or minimize churn

To increase retention or minimize churn

  • Her strategy is to do something special for people who are most likely to churn. 

  • She takes action by  sending people likely to churn a discount on a yearly renewal

  • They want to target specific people to give a discount.

  • She doesn't want to give a discount to the whole customer base

  • Target those people with some type of experience with the brand.

  • Quickly spot emerging trends and react to them

  • Quickly identify top customers

  • Select brand evangelists

  • Select recent purchasers

  • Dynamically target audiences in real-time

  • See real metrics across multiple data sources (like churn rate) 

  • Easily drill down into vast data lakes

Persona workshop objectives

  • Focus the team on the Primary User 

  • Unify and build consensus as a team

  • Get an early win and show value right away.

  • Learn about the "Jobs to be done"

  • I dentify "Pains and Pain Relievers"

  • Set them up for the Journey map exercise


I later I will validate their assumptions

Customer Excellence Team

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Monika the Marketer


Goals

  • Identify the most loyal customers

  • Identify the top spenders

  • Find Brand evangelists

  • Create brand endorsers

  • Retarget loyal customers

  • Harvest Social media dat

  • Integrate top spenders data

What does success look like?

  • Increased brand awareness

  • More purchases

  • Increased customer retention

  • Increased customer satisfaction

  • Higher Revenue

User Interview Results

Synthesize research to refine requirements
 

 Modern marketers need dynamic, intelligent controls in order to quickly and easily:

Engage

Integrate Unstructured Data

End-to-End Architecture  

Play nice with other CRMs

Engage

Easy to Start

Easy to Use

Easy to Scale

Engage

Visualized Data Insights

Contextual Campaigns 

Systems Integrations 

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Backstage Personas: Data-Ops

Larger organizations will have many people in each role, while smaller companies might have one person performing multiple roles.

 

Many data analytics teams fail because they are focused only on people and tools and ignore process, similar to a sports team with players and equipment but no game plan

Tertiary  Persons 

3. Data Engineer

Builds the infrastructure to perform analytics
 

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4. DataOps Engineer

Orchestrates and automates the data analytics pipeline

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1. Data Scientist

Creates algorithms to predict buying patterns, address questions or solve problems

2. Analyst Operations

Summarizes and synthesizes massive data,

communicating insights

Secondary Personas 

From data lakes to an store purchase

 

A journey map to capture the user's journey from the old system to the new 

 

Monika wants to create a cross-channel experience, including the context what the customer is doing, where and when.

 

What will she be feeling throughout her engagement with this venture?

Lets give her a challenge.

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How can we help Monika

Identify who has the highest propensity to
 
Buy a tent in Boston
in the dead of winter?

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Workshop Prompt

 

This is Monika's 1st day with our platform.

 

She has a new campaign she needs to promote.

North Face has a new winterized tent

they want her to promote for Christmas in Boston.

 

Sales on camping gear are traditionally 

very low in Boston this time of year.

 

How do we help her be successful with this Campaign?

Journey mapping is an iterative process

This in-depth journey map was shared, tested and modified and eventually validated
by engineers, sales, execs, marketers, and customer success teams. 

Stakeholders ranked tasks using methods including affinity mapping and value score voting.

Two Scenarios

On the plane

When the doors shut, you are sent points to spend in-flight.

In the store

When the receipt is printed, a contextual discount is sent to bring you back to the store. 

Sale
Baguette
Paying for Groceries
30% Discount Purple
Traveling by Air

The flow of data:

Event - Data - Insights

Insight

Often Marketers don't actually use data available to them because the data is not consumable and it's too difficult to get meaningful insight out of the data, in time, to take the right action.

The System Flow diagrams

Understanding how the Data Flows is one of the most important parts of the design process.

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Insight and Pivot

This is where we learned the missing part was integration and so later  Tibco Buys Scribe.

 

We also need the events processing application to be transformed and made accessible on mobile.

This helps identify the MVP and prioritize the design sprints.

Mapping the data

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Identifying the MVP 1.0

Key capabilities

What can we build and when?

I identified the MVP by getting them to vote on what was the most important part and doable.

Configuration is mandatory.

  1. Attributes 

  2. Conditions 

  3. Events processing

 

Kayaking

Design Solution



THE RIGHT CUSTOMER    
AT THE RIGHT TIME     
IN THE RIGHT CONTEXT

Agile Design iterations with the stakeholders.

Participating early in the design development phase makes Iterations faster, shortens the approval process, saves bandwidth, is more Agile.

Whiteboard benefits 

Deeper knowledge transfer

Less design review meetings

Faster Iteration on more concepts and layouts

Get down to the MVP and plan stages while designing

Rapidly test and iterate concepts viability

Faster approval times

Get to market faster

An example of how I drill down with participants.

What are the characteristics and preferences of your best customers?

Why?

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Data Insights

 

RFM - Recency is the most important factor.

RFM Customers who have purchased from you recently often spend more are more likely to buy from you again. This segment will get a higher rating than customers whom you haven’t seen for a while and who will get a lower rating.

How this relates to UI

 

The order of the attributes in RFM corresponds to the order of their importance in ranking customers. Therefore I start her off with some of the Standard attributes

like Name ID, DOB, Zip...

Samples come with default orders so she has something to start from. 

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Creating Attributes concept
 

Partners

The sales team tests with customers.

Test

I Run internal testing with our Internal marketing experts saves a lot of time.

 

Roadblocks

are potential opportunities I include engineers at every step to point out friction that can be smoothed.

 

Product Design Crit

Review with UX team in weekly design standups.

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Synthesis 

Monika the Marketer doesn't want to spend valuable time consuming the code configurations to get started. She wants to start driving better decisions quickly.

This leads to the idea of selecting audiences by combining charts of customer events, geo-locations, demographics, and many other attributes and conditions.

Validate

I validated that this technology already exists in-house and is possible to implement.

 

Testing market fit

Then I created clickable prototypes to test if there is a market fit for these interactive selectable analytics? Customers were very excited.

 

I iterated on the concept by exploring different entry points to see where they would show up and could we access the data at the point of the audience creation. I test the boundaries of our technology and our different engeering teams to see where the issues are. 

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Refining the concept

 
Analytics summary with Progressive disclosure details underneath

This concept would enable the marketer to self-build the criteria for audiences and visualizations. Test and make adjustments to get the answers she needs from the data all on her own. The Marketers Eng team to focus on building the core product by.

Designed with a Mobile 1st approach is a competitive advantage for enterprises giving their customers more flexibility to stay informed and react from anywhere.

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Challenges

Swimming in Nature

TECHNICAL CHALLENGES

Simplifying all of the systems

  • Many siloed data systems

  • It's difficult to deliver personalized engagement offers

  • Predictive is hard (both technically and operationally)

  • Testing and learning is inconsistent and not scaled

  • Making decisions fast enough is challenging for new digital channels

  • Lack of data driven understanding

  • Getting timely input and approval from stakeholders fast enough was challenging

Fixing Electricity Lines

How I overcame challenges

Listen carefully

Be nice and diplomatic

Increase morale 

Early success stories

Constant communication

Clarify expectations 

Involve Eng & PMs 

Empathize to gain their trust

Understand their motivation

Accept others' authority

Be assertive when necessary

Work to fix the real problems

Use data to validate

Helping Hand

What we learned

As the design iterations developed, we found a critical missing piece in Tibco's tech stack: There needs to be a Connection Hub.

The marketing industry needed easier integration between data systems.

 

Pivoting to better integration: 

At the time there was no easy way to connect different data systems quickly. 

If Tibco could solve the connector issue, they could become the connection hub.

This contributed to Tibco's acquisition of Scribe Software, a data integration software that helps CRM-Customer relation management, ERP, and marketing automation.

Examples of ERP system modules include product lifecycle management, supply chain management (for example purchasing, manufacturing and distribution), warehouse management, customer relationship management (CRM), sales order processing, online sales, financials, human resources, and decision support system.

"empowering a wide variety of users to quickly connect any digital asset using any integration style, including modern API-led and event-driven approaches, and to streamline business processes with no-code process automation capabilities."

Other outcomes

I went on to work with the newly acquired Scribe team to helped migrate

the Scribe Connector store to our cloud platform.

Integration Connector Marketplace

Final Outcomes

The result of this project helped showcase the need to update these other on-prem capabilities and transform them into cloud services.

I designed new interfaces for many of the other cloud applications also,

always thinking about Monka.

TIBCO Cloud Services 

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Cloud Events Web Studio

I also designed the Cloud-Events Web-Studio for the Tibco Cloud Platform. 

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Artifact and change managment

Artifact deployment

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The End

Helful group facilitation techniques

Here are some quick and effective techniques that are useful for aiding help make group decisions, idea generation, knowledge transfer, and raising morale.

 
1-2-4-All.  

A technique that facilitates rich conversation in small groups and integrates small groups ideas around an important issue or question.

 

25-to-10 (Crowdsourcing). 

A technique for quickly generating and rating ideas.

 

Voting with Your Feet (or post it if that awkward). 

A technique for engaging participants to express their views for or against a position by moving from one side of the room or the other.

Card Sorting. A technique of gathering and organizing ideas that draw on the knowledge of the whole group.

 

Field Trip around the Room. 

A technique used to organize how members of the group discuss several topics and integrate ideas on how to address them.

 

Gallery Walk. 

A technique that gets the whole room on its feet to take a walking tour of posters for flip chart pages that reflect each group’s answers to questions.

 

Knowledge Café. 

A method that fosters discussion about topics important to participants.

 

Popcorn Report. 

A technique for eliciting comments from those who feel moved to share.

 

Speed Consulting. 

A technique that draws on experiences of participants to advise another participant on how to address specific problems.

 

Speed Networking. 

A technique that gets all participants to reflect on a question and share their insights.

 

Storytelling. 

A technique of sharing the knowledge that incorporates the context, emotion, and tacit knowledge.

 

TRIZ. 

A technique that helps groups think creatively how to solve a problem or improve a complex process.

Action planning

Identify all possible actions and then group by affinity, vote, priortize, assign. 

There are many more