Embed Size (px)
Citation preview
WHITE PAPER
UNIFIED TRIGGER JOURNEY
Aditya KaliaSenior Manager
Chhavi GuptaSenior Consultant
Pankaj Chaudhuri Senior Consultant
Written by
December 6, 2019
EXLSERVICE.COM 2
Introduction
In the world of email marketing for online retailers, there are three main types of campaigns.
1. Planned marketing campaign: A company decides the messages and offers it wants to put out into the market and identifies the target audience. This is the most common type of campaign.
2. Lifecycle campaign: A predetermined set of messages are sent based on where a customer is in the buying cycle regardless of their behavior. In a perfect world, customer selection, messaging, and timing should be fully automated. A simple example of this is a publisher sending a welcome email after someone subscribes and then, as a subscription nears its end, ramping marketing back up to drive a renewal. The common thread between these two campaigns is that the company is driving marketing messages.
3. Customer behavioral trigger campaign: This type of campaign differs from the other two in that the marketing messages are designed based on customer activity on digital channels like websites or apps. These customer actions are responded to in order to increase customer engagement and thereby their lifetime value.
In this paper, the third type of campaigns are referred to as triggers. The philosophy behind this is simple - All actions customers take on a website or app should be inferred as customer intent.
Marketing campaigns typically revolve around trying to understand customer interests and disinterests. The most scientific and value-generating of these campaigns are those based on customer activities commonly referred to as triggers. A trigger is when customer activity shows some form of intent. The majority of online retailers deploy triggers in some form to tap into potential revenue and customer engagement. However, individual trigger campaigns may not be the most optimal, as they may not be synchronized and coherent. This paper discusses the problems with individual trigger campaigns for online retailers, looks at the different aspects of trigger campaigns from a customer journey lens such as timing, content, and messaging, and proposes various methodologies for combining multiple customer journeys into a single unified journey. The proposed solution has gone live in one of the largest online retailers in Europe. The scope of this paper is limited to email digital marketing channel for contacting customers.
ABSTRACT
Salient components of a trigger campaign
The salient components of a trigger email sent in response to customer’s online activity are:
EXLSERVICE.COM 3
• How do is the intent defined and identified? Is the activity deserving a contact?
• How and when should the customer be contacted?
• Should the frequency and messaging vary by customer type?
• How should the testing solution be set up with the objective of understanding the impact of trigger communications?
Trigger Emails: Overview, Framework & Potential Solutions
Identify the right relevant activity, referred to as a touchpoint in rest of this paper, is the most important component of a trigger email framework. However, what happens in a scenario where a customer has done a lot of activity in one day, resulting in many actions that qualify for a contact? Contacting the customer for each of these actions is not the best customer experience, and increases opt-out risk. Therefore, an overarching framework is needed to help to arbitrate among the customer’s eligible trigger emails and aid in maintaining the optimal contacts for that day.
The optimal number of daily trigger touchpoints varies from one organization to another. For our client, the rule was sending a maximum of one trigger email per day. However, the question still remained of how to choose the best trigger email for a customer from all the eligible options?
Three arbitration approaches that were tested.
1. Hierarchy based: In this approach, the trigger email’s strength is measured by the customer activity’s proximity to conversion. For example, abandoning a basket is closer to purchase completion than browsing a product. Therefore, a trigger communication with a message about the abandoned basket is more important than the one about the product browsed. A hierarchy is defined to arbitrate among the day’s eligible messages for a customer based on their position in the purchase funnel. The benefit of this approach is the simplicity of execution and maintenance. However, the downside was one-size-fits-all methodology for all customers, and the belief that the event closer to purchase is always more valuable than the ones before it.
2. Score based: In contrast to the previous approach, this approach also weights the product included in the activity as well as the customer’s position in the purchase funnel. The hypothesis is that some products are better than others based on margin, customer interest, and other factors. A composite score* of activity strength, or position in purchase funnel, and the interacted product strength, based on factors such as product reviews and overall sales for that product over the last few days, is calculated for all eligible trigger messages for a customer on that day. The message with the highest score is then sent to the customer. The benefit is personalized message prioritization for every customer. However, the downside is that in majority of the cases, same product appears in different stages of the web-session. For example, in order to abandon a product, a customer must browse that product – and will often browse it more than once. In such a scenario, the abandoned basket message will cannibalize the messages related to upstream activities like single browse, repeat browse, and others. This challenge led us to the next approach: The combined trigger methodology.
*Score = f (Profit, Customer Interest, Activity & Product trend)
Hierarchy Based
Score Based
CombinedTrigger
EXLSERVICE.COM 4
driven messages in the trigger contact. However, there needs to be a constraint on the length of the email to keep it crisp and short. Therefore, the first step was to build an algorithm that selected the most important and relevant products for the customer from the ones that the customer interacted with. This algorithm considered three factors:
1. Profitability of the product: The hypothesis is that the product’s historic profitability can be an indicator of the future profitability. Therefore, historic profitability of the product was chosen as one of the three factors.
2. Trend: Another important factor is the general perception of that product in the market. This is defined as the number of times the product has been viewed by all the customers in the last couple of days.
3. Customer’s Recent Activity: The third factor is the strength of customer activity. The recent activity of the customer is more important than previous activities. Therefore, the number of days since the last activity was the third variable.
When should the customer be contacted?
Various studies show that keeping the first touch point within a few hours of the activity is the most value generating. However, due to technical limitation of our inability to contact the customer on the same day as activity, the earliest contact in the journey discussed in this paper is next day from activity (Day -1 Email).
In line with most of the successful activity-driven email campaigns, a multi-follow up approach was defined. Follow ups were sent after specific intervals. These intervals were arrived at based on past data and seeing the typical gap where customer responses are optimal. The gap between first contact and subsequent follow-ups has been kept same for all the customers and product types in the first phase of implementation.
3. Combined Trigger: Besides the challenges in arbitration in the previous two approaches, another downside was the incoherence in the customer journey. Since the above approaches allow for selecting the most suitable trigger email from the ones available on a given day, the outcome can result in a disjointed customer journey where each day’s message comes from a different customer activity, and is sent without keeping any common thread across the days. In the combined trigger approach, relevance and consistency in the trigger contacts over the days is introduced while maintaining the frequency of maximum one message per day.
METHODOLOGYConcept
The concept of a combined trigger approach is to tie up loose ends in individual triggers and design a single synchronized, coherent journey for a customer, as opposed to multiple incoherent journeys. In other words, the content and message from different available trigger emails are combined across the days to maintain consistency.
Which triggers should be combined?
An analysis on pre-arbitration available trigger emails over a three month period helped identify that the majority of the instances with arbitration included one or more of three triggers: abandoned basket, repeat browser, and save for later. Since all these triggers correspond to important milestones in the customer’s conversion journey, by choosing only one of these due to the arbitration process, a large portion of the relevant messages for the customer are lost. Therefore, these three triggers can be combined together.
How can the content be combined?
The main objective of the combined approach is to maximize the number of products and customer activity
EXLSERVICE.COM 5
Impact on timing: An email is always sent on the next day of eligible activity. Any previous live journey is ended, and a new journey is started from that day. All previous follow-up emails are cancelled, and the subsequent follow-up emails are scheduled as per the new Day-1 email.
Impact on content: In this scenario, the products from the latest eligible activity are added to the list of the previous eligible products, and the scoring mechanism identifies the required number of the most relevant products for the next day’s emails. The next day’s email acts as the Day-1 email for the qualifying products from the latest eligible activity, and follow-up email for the qualifying products from the previous activity. A qualifying product can be included in the journey only if:
1. It has not already been included a certain number of times in the past journeys so as to incorporate soft customer feedback for disinterest in the product
2. The activity leading to the product’s inclusion in the journey is not obsolete, meaning the customer recently interacted with it
Once the product fails to satisfy either of the above two conditions, it is no longer included in the mix of products competing for inclusion in the combined trigger email.
How does customer activity impact content and timing?
The customer’s activity while in a live journey will impact their subsequent journey content and timing. Mentioned below are a few situations a customer can enter while in a live journey. Here, activity is defined as eligible activity if it consists of the activities involved in the combined trigger approach: abandoned basket, repeated browse, or save for later.
• • Scenario 1: The customer enters a journey and does not do any other eligible activity while in the journey
In this scenario, there is no change in the content across the days, with reminder emails sent for the same products as in the Day-1 Email. The journey is completed when all the follow-ups have been sent.
Illustration: Standard Journey
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Customer does activity and qualifies for the proposed journey
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
An email is sent to the customer as a response to the activity, reminding them to complete the purchase by including top products customer interacted with
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Owing to no response from the customer, and in an attempt to remind the customer of the activity, the first follow up email is sent
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
As a last throw of dice, one last follow up email is sent
• • Scenario 2: The customer enters a journey and does additional eligible activities
EXLSERVICE.COM 6
Illustration: Non-Standard Journey
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Customer does activity and qualifies for the proposed Journey
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
An email is sent to the customer as a response to the activity, reminding them to complete the purchase by including top products customer interacted with
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Since customer has desirably responded (but not purchased), it prompts pull forward of the erstwhile planned follow up on Day 5 to next day i.e. Day 4. The contents of this email will be a mix of products customer interacted with on Day 0 and Day 3
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Day 4 email is a first follow up for Day 0 activity and first email for Day 3 activity
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Same as customer behaved on Day 3, and hence our response will also be in-line
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Day 8 email is a second follow up for Day 0 activity and first follow up for Day 3 and first email for Day 7 activity
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Day 12 email is a second follow up for Day 3 activity and first follow up for Day 7 activity. There is no content from Day 0 as the activity is archaic enough
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Day 22 email is a second follow up for Day 7 activity. There is no content from Day 0 or Day 3 as the activities are archaic enough
How do customer actions impact the journey?
Once a customer undergoes a journey, it is imperative to regularly record and react to their response. This is one of the prime reasons for pulling forward the follow up emails as explained earlier. This section examines scenarios for customer responses and the planned changes to the journey.
1. Customer makes a purchase: The journey achieves its objective when the customer completes the purchase. The live journey is closed at this point. However, it is more than likely that the customer has not bought all the products they interacted with. In this case, these products can be used in either the post-purchase journey, or as customer-specific product recommendations in other emails.
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
STOP
Customer makes purchase on Day 3 and the journey is stopped
EXLSERVICE.COM 7
2. In subsequent activity, customer shows interest in a new product: This is one of the most frequently occurring phenomenon. While the customer is in a live journey, they also visit the website and browse some products not in the current journey. In this case, the new products are added to the list of the customer interacted products, and the scoring algorithm is used to identify the suitable products to be included in the email as explained in scenario two above.
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Customer already in journey visits website again on Day 3 and views new products
Day
Action
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Customer receives email on Day 4 which includes products from Day 1 as well as Day 4 activity
3. In subsequent activity, the customer shows interest again in a product already in the live journey: This is the most challenging. There are many schools of thought as to how to tackle this tricky situation:
• Consider the latest occurrence of product interaction for scoring: While this seems the simplest, it misses an important consideration. This will ignore the interest the customer showed before the last interaction.
• Consider the earliest occurrence: While this overcomes the limitation of the previous approach of capturing historic activity, this ignores the recent activity. This will also give a low score for this product in recency which intuitively seems wrong.
• Consider all occurrences: To overcome the
limitations of short-sightedness and longevity, the approach adopted is scoring all occurrences of products, and then adding the scores for different occurrences of the same product.
When does the journey end for the customer?
A live journey ends for a customer if any of the following happen:
• Customer makes a purchase: In this scenario, the live journey is ended and the non-purchased products are passed on to form a part of recommendations for the post-purchase journey
• Customer does some eligible activity while in the journey: The current journey is ended, and a new journey starts for the customer
• All follow-ups are used: If all follow ups for the product have been used, the journey with those products is ended
BENEFITS & LIMITATIONSBenefitsThis journey was implemented for an online retailer and produced results which are mentioned below. Such a journey can be implemented for any digital retail or subscription business to improve conversion. The following are some of the observed benefits:
• Incremental Margin and Revenue Improvement: 3% uplift in margin and 2% uplift in revenue
• Increased Open Rate: 2% uplift in email open rate and 0.3% uplift in click rate as compared to the individual triggers
• Increased Customer Engagement: 2.8% increase in customer engagement, calculated using internal customer engagement score
EXLSERVICE.COM 8
Next Steps
Learnings from this experimentation process can be used to include other type of marketing communications like service emails, end of season sales, and new product launches. The data collected in this phase will serve as a test bed for deep learning algorithms. Learnings from email channel can be replicated across other CRM channels such as SMS, push notifications, onsite personalization, and social media platforms such as Facebook, LinkedIn, and Twitter to make customer journey seamless and truly personalized.
• Improved Conversion: Customers receiving this journey had 1% higher conversion than the existing distinct triggers ecosystem
Limitations
This part of the paper focuses on the limitations in the current approach and lists alternate approaches that can be explored:
• Currently the product scoring methodology is heuristics based. AI and deep learning techniques can be used to further experiment with product recommendations. The learnings and data collected in first phase of test should be an enabler for this.
• Current methodology ranks the scores to identify product recommendations. Methodologies using absolute model scores can be explored.
• The scoring methodology treats everyone in the same way. Since different customers respond differently to different marketing communications, customer response patterns can also be included.
• A very basic limitation of this journey is the timing. For frequent website visitors, who browse products regularly but do not purchase, the number of emails they receive will be very high. Some rules around contact frequency can be incorporated to combat this.
EXLSERVICE.COM
GLOBAL HEADQUARTERS320 Park Avenue, 29th FloorNew York, New York 10022T +1 212.277.7100 F +1 212.771.7111
United States • United Kingdom • Australia • Bulgaria • Colombia • Czech Republic • India Philippines • Romania • South Africa
EXL (NASDAQ: EXLS) is a leading operations management and analytics company that designs and enables agile, customer-centric operating models to help businesses enhance revenue growth and profitability. Our delivery model provides market-leading business outcomes using EXL’s proprietary Digital EXLerator™ Framework, cutting-edge analytics, digital transformation and domain expertise. At EXL, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation and logistics industries. Headquartered in New York, New York, EXL has more than 29,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), Latin America, Australia and South Africa.
This article is not intended to constitute legal, compliance, regulatory, privacy or similar professional advice, and EXL does not provide services to clients in those areas. The reader is advised to engage experts to provide professional advice on any legal, compliance, regulatory or privacy topics covered herein. For more information, see www.exlservice.com/legal-disclaimer
© 2019 ExlService Holdings, Inc. All Rights Reserved.
