Email Campaign Challenges

How Data Science can solve Email Campaign challenges

The power of this digital world is that we can measure, quantify, and qualify pretty much everything you want to analyze. Why don’t we use these capabilities of this digital spectrum for our core marketing activities as well? When it comes to marketing, still emailing is one of the basic and important activities which every marketer needs to handle on a day-to-day basis. But in this very competitive market, handling emails in terms of targets, contents, quality, and even the time which we should send the emails are very important for better outcome and results.

Here the Data science will play a pivotal role for the Email campaigns and management regarding the effectiveness, quality, and other elements. Basically, there are, few factors that are very important for each campaign, such as customer segmentation, data segmentation, personalization of emails, Campaign/Email Optimal Timings, Content Automations for reducing the campaigns turnaround time and optimization of the Email templates, and many other areas in which Data science can bring measurable results.

Customer & Data Segmentation – Data Science (AI/ML) can segment the customer base along with Email list segmentation helps to increase open click rates, conversations, and CTRs. Likewise, in Data Segmentation, we can define rules for sending emails to prospects (whom to send to).

Email Subject Lines Corrections/ Optimizations – Data Science (AI/ML) algorithms can be used to analyze the results of the marketing campaign to optimize and improve the email subject lines over time, and this will result in a higher click-through rate for each email campaigns. 

Predictive Analysis & Email Personalisation– Data Science (AI/ML) can be used to send tailored emails to each customer based on the customer behavior, interest, and preferences along with ML recommended product/services that a particular customer is likely to be interested in.

Determining Optimal Timings for Emails- Data Science (AI/ML) algorithms can predict the best time to send out the email campaign to optimize engagement based on customer’s past interactions and demographics details.

Email Delivery Time optimization – Data Science (AI/ML) algorithms can determine email delivery times based on when recipients are most likely to see and open messages.

Data Cleansing – Data Science (AI/ML) can automate the email list clean-up process based on out-of-date contacts and changed job titles, phone numbers, and other information.

Email Promotions – Data Science (AI/ML) can determine the optimal offer for each customer, and this will help the marketer to customize the promotional offers to each customer.

Retargeting – Data Science (AI/ML) can distinguish different types of customers to send the retargeting emails at an optimal time.

Khalil Sheikh

Khalil Sheikh

Khalil Sheikh is the Executive Vice President of Solutions and strategy at Saxon. Under his leadership, Saxon is building ROI driven Data Science AI/ML and recommendation engines for its fortune 1000 customers. Khalil has extensive experience in the Software & IT services industry and in turning around businesses through actionable business intelligence leveraging AI. With more than 28 years of experience across the industry verticals, he has led several successful Data Science & digital transformation journeys for ISV’s and enterprises. He led CTO/CIO forums in the valley and is known for fostering creativity, collaboration, and diversity.