SendSmart Web App

SendSmart is a web application utilized by Auto Dealerships to increase customer engagement through automated messaging. According to SendSmart, their solution can be expected to double web lead response rates.

Role

UX Research & Design

User Surveys & Interviews
Affinity Diagram
Empathy Map
User Personas
Signal Detection
Problem Statement
Ideation
Feature Prioritization
Competitor Analysis
Task Flows
Wireframes & Prototype
Usability Testing & Analysis
Iterations

Team

Solo Project

Tools

Figma
Miro
Google Suite
Zoom

How does SendSmart work?

The Problem

Dealership representatives have reported SendSmart doesn't allow them to organize and filter their messages and notifications. This makes it difficult to detect and navigate their assigned customers, which could result in lost opportunities.

Proposed Solution

Increase dealership representatives’ sensitivity toward detecting their assigned customers by providing ways to discern them from the pool of customers being assisted by other team members. This includes adding a personal inbox, improving the layout for key identifiers to be displayed, and adding personalized notifications.

User Research

User Surveys & Interviews

Six dealership representatives were surveyed about their use of SendSmart. Follow-up interviews were conducted after narrowing down their pain points and blockers.

Topics Explored:

  • What type(s) of dealer representatives use SendSmart?

  • How helpful is the message notification system?

  • How easily do dealer representatives navigate messages?

It became apparent that some responses differed depending upon job title / position.

Affinity Diagram

To analyze the data further, an affinity diagram was constructed to find patterns among responses.

Additional Key Findings:

  • SendSmart is used for different reasons based on job title / position

  • Dealer representatives use SendSmart most days on both desktop and mobile devices

  • Auditory & visual notifications are utilized by dealer reps on both desktop and mobile devices

  • Notification preferences vary by job title / position

An additional diagram showing the dealership process was made to provide context.

Empathy Maps

Using qualitative data from both user surveys and interviews, multiple empathy maps were developed to better understand the experience of the different types of dealer representatives.

BDC Representative

BDC Manager

Appraiser / Salesperson

User Personas

Each persona represents a different user segment of SendSmart. Their development was guided by the empathy maps above.

BDC Representative

BDC Manager

Appraiser / Salesperson

Defining the Problem

Signal Detection Theory

Based on the user research, there are dealership representatives who experience pain points and blockers with regard to filtering and detecting their assigned customers. This can be expressed in terms of Signal Detection Theory (SDT).

If needed, a brief overview of SDT is provided below.

Signal Detection Theory | Brief Overview

Signal Detection Theory can be used to understand situations wherein an operator detects whether a signal is present or absent. In this case study, it applies to whether a dealership representative detects their customer’s message. Their internal response is categorized as either “Yes” or “No”.

Signal and noise can be modeled using distribution curves. In most situations, there will be at least some overlap between the noise distribution and the signal distribution. The overlapped region is where breakdowns in performance occur.

“Yes” / “No” Response

“Yes” Response: If the signal is present, it’s a HIT; if the signal is absent, it’s a FALSE ALARM.

“No” Response: If the signal is present, it’s a MISS; if the signal is absent, it’s a CORRECT REJECTION.

Response Strategy (Bias)

The operator can bias their internal response to lean liberal (i.e. responding “Yes” more frequently) or conservative (i.e. responding “Yes” less frequently). This can be used as a strategy to maximize their HITS or CORRECT REJECTIONS. However, a trade-off will typically occur, resulting in a higher occurrence of FALSE ALARMS or MISSES.

Sensitivity

Sensitivity is represented in the model as d’ (d-prime). This is the measure of separation between the signal and noise distribution curves. The greater the separation, the higher the sensitivity.

When increasing sensitivity, it becomes easier for the operator to discern the signal from the noise. This improves their performance by increasing the probability of HITS and CORRECT REJECTIONS, while decreasing the chance of FALSE ALARMS and MISSES.

When decreasing sensitivity, it becomes difficult for the operator to discern the signal from the noise. This weakens their performance by decreasing the probability of HITS and CORRECT REJECTIONS, while increasing the chance of FALSE ALARMS and MISSES.

SDT Application to SendSmart

SDT applies to personas unequally.

BDC Representative

The BDC representative uses SendSmart to actively engage with customers in real-time. To do this, they must sift through the noise of notifications/messages of their teammates in order to detect their assigned customer’s signal. Because this noise is excessive, they often experience false alarms. This leads to representatives taking a more conservative response to incoming notifications and messages, resulting in an increased probability of missed opportunities.

BDC Manager

The BDC manager uses SendSmart to passively monitor their team’s conversations to ensure quality. Unlike the BDC representative, the manager is interested in all the conversations as they happen and doesn’t perceive the high volume of notifications and messages as noise. However, it is difficult to evaluate individual performance given the inability to filter messages by user.

Appraiser / Salesperson

The appraiser / salesperson refers back to conversations in SendSmart to get up-to-speed on the customer’s situation before they arrive at the dealership. Much like the BDC manager, they generally don’t perceive the high volume of notifications and messages as noise. However, if an appraiser / salesperson decides to message a customer using SendSmart, they’ll find themselves dealing with the same detection issues as the BDC representative.

Problem Statement

By framing the issues dealership representatives face in terms of SDT, it helped to develop a concise problem statement to be considered for the design phase:

It has been observed SendSmart doesn't afford dealership representatives the ability to sort and filter their notifications and messages making it difficult to detect and navigate their customers, which leads to missed opportunities.

Ideation

How Might We ... ?

How might we boost dealership representatives’ sensitivity toward detecting their customers’ signals so as to increase HITS and decrease MISSES? How might we inhibit the noise they experience so as to lower the probability of FALSE ALARMS?

How might we redesign SendSmart to result in a signal / noise distribution similar to the one below?

Current UI Design

The current UI design only displays the names of customers who have responded (blurred) No other indicators are present for determining which dealership representative is working with which customer.

Having both top and side navigation was identified as being problematic. During user interviews, it was discovered this feature leads to confusion in terms of navigational hierarchy.

“I Like, I Wish, What If?”

To generate ideas on how to approach this problem, an exercise using the “I like, I wish, what if?” method was performed.

Competitor / Familiar Application Analysis

The personas’ use of familiar applications was analyzed for the purpose of examining their existing mental models. The idea behind this exercise was to take these cognitive mappings into consideration for approaching a design solution to SendSmart.

DealerSocket and Gubagoo were selected given their in-app messaging features.

Key Takeaways:

  • SendSmart distinguishes itself by featuring automation as part of its messaging application

  • SendSmart is the only messaging app that doesn’t provide a personal inbox to users

  • Gabagoo implements a “My Chats” tab to separate an individual user’s messages from their teammates’

  • Both DealerSocket and Gubagoo notifies representatives for only their assigned customers

  • Both DealerSocket and Gubagoo utilize a collapsible sidebar

Feature Prioritization Matrix

Potential solutions generated in the previous exercises were placed into a prioritization matrix to determine which features should be selected. Priority was placed on features predicted to have the greatest impact (based on user research) and least complexity (in terms of design).

Using this method, the following design solutions were selected:

  • Display lead assignments within the inbox

  • Personalized notifications

  • Ability to sort/filter messages

  • Personal inbox

  • Collapsible sidebar

Design & Prototype

Task Flows

Two features implemented in the redesign: the ability to (1) filter messages and (2) set up personalized notifications. Flows were created for each task.

Filter Messages

Set Up Personalized Notifications

Sketches & Markups

Sketches and markups over the original design were made to better understand the spacing requirements for each added element.

Sketches

Markups

Digital Wireframes

Digital wireframes were designed and prototyped.

Improved Inbox

Various elements were added or redesigned to help boost representatives’ sensitivity toward detecting their customers’ signals.

  • Top navigation was integrated into side navigation to avoid confusing hierarchy

  • Side navbar was redesigned as collapsible to afford more space in the inbox

  • “Team” and “My Messages” were separated to help representatives discern their own messages from the team

  • Ability to filter messages by source and/or representative was added

  • Additional identifiers were displayed in each message field: lead source and assigned rep

Personalized Notifications

To inhibit the noise dealership representatives experience, personalized notifications were added as a way to help silence the excess amount of notifications related to their teammates’ customers.

Testing & Iteration

Usability Testing

Six usability tests were conducted to evaluate the redesign - three were performed remotely via Zoom, and three were conducted in-person. Participants were instructed to complete four different tasks.

Objective

The objective was to test and observe whether participants naturally use newly implemented features for filtering messages.

Tasks / Prompts

Task 1: Filter messages using My Messages

Where would you go to view only your conversations?

Task 2: Filter messages by user

Filter messages to determine how many contacts have been assigned to each user

Task 3: Filter messages by lead source

Determine which lead source has provided the most leads

Task 4: Change notification settings

You no longer want to receive notifications for leads assigned to other reps. How would you change your notification settings to reflect this?

Analysis

An analysis was madve on each task. Success was based on whether a participant was able to complete the task on their first attempt. Participant feedback was considered.

Iterations

Based on testing and feedback, iterations were made to the side navigation bar and notification settings.

Side Navigation Bar

The iconography was reconsidered after several participants expressed confusion and dissatisfaction with the gear symbol being used to represent “Account”. Taking this feedback, a user symbol with a squared background (to differentiate it from “Contacts”) was used to replace the gear symbol for “Account”.

Since most participants associated the gear symbol with “Settings”, most had made the error of selecting “Account” to update their notifications. Given this, notifications was given its own category under “Settings” in the sidebar (with a gear symbol).

Notifications Settings

Under “Team” notifications, participants found the wording of these options to not be descriptive or self-explanatory. “Unassigned Contacts” was changed to “Contacts that haven’t been assigned yet”; “Assigned Contacts” was changed to “Contacts assigned to my teammates”.

Reflection & Next Steps

Reflection / Limitations

Small Sample Size

Multiple personas weren’t expected to be utilized at the beginning of the project, as a single “dealership representative” persona was thought to be adequate. After further investigation, it became apparent the goals and needs of users depended upon their job title / position. As a result, six dealership representatives were considered across three different personas, averaging only two reps per persona. Due to there being a low sample size, conclusions about the personas may not generalize as hoped.

Single Dealership Consideration

The data in this case study was conveniently sampled from a single dealership as a way to streamline the research phase. While this method allowed data to be collected in a short period of time, it may have come at the cost of having a more holistic view of dealerships and the processes they implement. It could be the case that pain points one dealership experiences when using SendSmart aren’t the same pain points of another dealership. Once again, findings may not be as generalized as hoped.

Next Steps

Testing

Further testing should be conducted. In particular, the replaced iconography in the sidebar and the new wording within the notification settings should be tested to confirm if they translate well to dealership representatives.

Missed Opportunity Rate

Missed opportunities should be recorded before and after implementing the redesign to confirm if a decrease in the rate at which missed opportunities occur.

Research

Research involving a larger sample size across multiple dealerships should be conducted to increase confidence in the ability to generalize findings. This will also lead to the development personas that better represent various user segments of SendSmart.

Additional Features

Based on user research, additional features should be considered to improve dealership representatives’ experience of SendSmart. Areas to be explored include the implementation of CRM integrations and individual performance metrics.