Apricot Marketing AutomatCase Study.pdf

Casestudy

1. Salesforce
Personalization Studio
Case Study

2. The Challenge


Apricot Clothing, a popular UK-based fashion brand, is renowned for
offering a wide selection of stylish and affordable women's apparel, from
dresses to outerwear. However, they encountered a notable challenge
related to the absence of personalized communication with their
customers. Generic marketing messages and recommendations
hindered their ability to engage and retain shoppers effectively.

This lack of personalization led to a drop in revenue as customers were
less inclined to make purchases, resulting in missed sales opportunities.
Additionally, Apricot Clothing struggled with declining conversion rates
on their website, where many visitors browsed products but didn't
complete transactions, affecting their bottom line. Addressing these
personalization and conversion issues became crucial for sustaining
their position in the competitive fashion market.

3. The Goals

















Utilize Interaction Studio for
personalized recommendations
and enhanced user engagement.

Reduce overall Abandon cart and
Abandon Browse

Elevate the overall customer
journey for a better shopping
experience.

Increase customer lifetime value
by delivering added value to
customers.

Ultimately, boost member retention
rates for long-term customer loyalty
and business growth.

4. The Approach


We conducted a detailed discovery workshop to understand where interaction
studio could be most impactful for Apricot. After delving deeply into Apricot
business model and objectives. We formulated a series of phased use cases.

During the outset, personalization was introduced in four critical areas.

1.Understanding user behaviour on the website to get a sense of what
they were browsing
2.Tracking Users who have not completing Transaction and Abandoning
their Carts
3.Post onboarding users, providing users with top trending products to
choose from
4.Tapping back into customers who had not interacted with the brand for
a long time
5.A Strong Product Recommendation engine built using Einstein to
provide 1-1 Recommendations for each user

Pushing the data points derived from above 4 areas into Marketing Cloud, to
initiate a omnichannel Journey and ultimately converting them

5. The Results
Overall Abandon cart has reduced by 32%
Conversion of Abandon Browse user has gone down by 25%
Website traffic has increased by 8% considering the 1-1 Personalised communication being sent out
Email Open Rate has improved by 37%
Overall the Marketing Team effort in Managing platform has reduced drastically which is helping them focus on Strategic
initiatives

6. Thank You