Daffodil helps one of the leading retail technology companies
re-engineer their flagship CRM platform

Team Daffodil started by auditing the code-base of their existing CMS platform to understand the part of code that can be used in the new CMS. Since the former solution was built on an outdated technology, it was necessary to refine the usable part of the code before integrating it with the newer one. Our business analytics and software architects outlined the optimal architecture of the platform, refined the functional requirements and developed a complete product vision and its development roadmap.

Daffodil software developed a cross platform web based CRM platform that automates the entire array of tasks related to day to day functioning of a sales team of a retail outlet. As much as 30% of the code was reused in developing the new CRM, which resulted in significant savings in time, cost and development efforts. The primary focus was placed on increasing the user-friendliness and granular level customization of the system. A large set of functionalities were incorporated to seamlessly manage customer, product, and sales information which could help retailers in improving their sales, customer loyalty, and execute marketing/promotion campaigns.

Depending upon the role, such as store manager, store associates, brand admin, area manager, etc. corresponding activities could be performed in the CRM. For example, the store associates can keep track of their customers like their last purchase, price-value of their purchase, the net worth of their purchases so far. Likewise, they can figure out the customers who haven’t shopped from the last three or six months and engage them to improve loyalty.

During development, team Daffodil had to ensure service continuity, scalability, and cost into consideration. For that, the CRM’s infrastructure was built on Amazon Web Services (AWS). For application server hosting, Amazon Elastic Compute Cloud (EC2) service was utilized and for managing and scaling the relational database, Amazon RDS service was used. For seamless development, test, and release of the solution, our CloudOps team continuously checked for backend connectivity, security implementation, load maintenance, cloud usage for various activities such as S3 for image optimization, upfront capacity planning, etc.

Since the requirement was to make the solution scalable, Amazon Elastic Load Balancing service was utilized. The load balancer ensured that the resources scale up or scale down as the requirement strikes. Since small and multiple instances were used instead of a single server, it saved 30-40% of the operational cost for the application. All images and static data in the application was saved on Amazon Simple Storage Service (S3). The S3 images are served through Amazon CloudFront for quick retrieval of images in different geographical zones.

For securing the application against third party attacks, Amazon Web Application Firewall (WAF) was used. WAF has a predefined set of rules that recognizes common attack patterns such as DDoS, SQL injection, or cross-site scripting and blocks them. Along with this, Sucuri Firewall protection was used to speed up load times of the CRM.

Some of the key features and their enablement technologies that we incorporated in the CRM platform are:

• For direct communication with the customers and marketing/promotional campaigns, the CRM is integrated with Whatsapp, iMessage, and email channels. For SMS and emailing predefined, multilingual templates are provided in the CRM solution. For emailing, Sailthru API was used. Along with the emailing provision, the API allows saving the stats such as email open/view rate, click-through rate, etc. These stats are visible to the CRM users.
• For audio/video communication between the customers and offline store associates, a custom video conferencing module is integrated within the CRM solution. The module in the CRM was customized using the Twilio SDK.
• The CRM generates reports in tabular and graphical format. The report can have different types of information like customer purchase history, active/inactive sales associates, the number of customers SAs followed up with, customers with 50% or 90% profile completion, customers with purchase value within a price range, etc.
• For quick retrieval of data from large datasets, having multiple conditions, MYSQL views are created. The large data queries were converted into short tables and then those queries were converted into MYSQL views.
• The CRM solution is multilingual. Depending upon the store location, the CRM language can be switched to English, Arabic, German, French, Japanese.
• For improved user experience, the CRM on the mobile web has the push notification option so that the store associates can timely check for updates in the notification tray.