“How to Use Big Data For Better Advertising and Promotions?”

A speech given by Francis Kwok – Founder of Radica Systems Limited, at Big Data and Digital Innovation 2015, held by Marketing Magazine.

In the age of Big Data, marketers all over the world are all putting their soul and minds in adopting Big Data into marketing, intending to truly know about their clients, and smartly push the right kind of information to attract targeted customers, so in order to make wise marketing decisions, aiming to increase the company’s revenue at the lowest cost possible. But how?

There are 4 major problems often faced by marketers nowadays when wanting to make wise marketing decisions: “How to do multi-channel marketing?”, “How to lower the cost and get more creative on forming key word and lower the price with higher response rate?”, “How to do segmentation?”, and “How to make smarter content?”

Problem 1: “How To Do Multi-Channel Marketing?”

These days, most of the companies already own a single data base. In that certain single data base, marketers combine data such as customer prospects, data on customers’ social media usage, putting all of these into one single data base. That is where the problem lies, marketers often neglect the fact that the contexts of these data vary; since customers might use very different social media platforms, it could be WeChat, Facebook, or some might simply stick with a mobile phone, email, etc. So, how may marketer unify the data collected from various marketing channels effectively?

Problem 2: “How To Do Segmentation?”

Once marketers find the appropriate channel to promote to their customers, another crucial challenge that comes along is customer segmentation. Over the years, the importance of segmenting customers has been recognized. However, up to now, marketers should bear in mind that simply segmenting their customers is not enough; marketers need to go beyond that! For example, one of RADICA’s customers Global Sources, it has to do more than 200 segmentations every week. The segmentation of their customer changes so fast that it has to constantly catch up with its customers in order to  keep up with its high volume of sales. Now most marketers may wonder: How to play smart in customer segmentation then?

Problem 3: “How to Lower the Cost and Get More Creative in Forming Keywords and Lower the Price with Higher Response Rate?”

Search Engine Marketing (SEM) - For marketers, if they would like to do search engine marketing on Google, let say many of them are wanting the same keyword, they need to pay higher price in order to beat the fellow competitors for that certain keyword. Those who can afford a higher price win in this game. Such situation is beneficial to Google; however it would be a hassle for marketers with all the competition, not to mention spending a large amount just for the sake of a keyword. So, how can marketers get to use their desired keyword at a lower price, and with a high response rate?

Problem 4: “How To Make Smarter Content?”

With the establishments of different social media platforms, the trend of digital marketing, and the overwhelming popularity of Big Data these days, no doubt marketers have so much content planning that they need to work on. Taking a customer of RADICA as an example, as a company in the insurance field, it has to give at least 6 types of content to a specific group of customers in order to get better marketing result. Efficient content is vital to markers in such case. Now, what makes the content efficient?


The above problems could not get to marketers with one well-rounded marketing solution, yes, just one- RiMANGGIS (The latest version of RiMANGGIS will be launched in October.)

RiMANGGIS is a big data direct marketing platform especially for experienced marketers who would like to make wise use of big data for a more automated and efficient communication with their clients. It helps marketers to analyze the appropriate channels for customers, deliver personalized message to targeted customers at a high response rate.

RiMANGGIS smartly uses the big data analysis engine to real-time update with customer preferences. It does not simply use the company’s single data base but it helps to combine internal and external data to help marketers to be more precise when it comes to making marketing decision. Plus, it also sends the right message to targeted customers through the right channel at the right time. For example, if the customer tends to open email more than he or she opens an SMS text, RiMANNGIS knows which channel to get to your targeted customer, saving marketers cost and time efficiently! Simple as that.

What is more?  In case a campaign fails to get to the targeted customers, RiMANGGIS has an engine that tries to use one single campaign to help marketers re-render to different channels, such as email, SMS (we call SMS Plus) which is very popular in both Hong Kong and China. One important note: having a catchy subject line in your email and SMS helps you to track customer data and might as well push the message to WeChat or any app notifications to attain a 2-factor based response from customers. In that way, you may prioritize which channel to deliver first, if the response rate is low, marketer might as well promote its products in another channel. Easy.

RADICA and New Media are now in alliance, coming together to help marketers build the appropriate and effective eDM content. How? Through combining the internal knowledge and different big data collected from different learning layers. With the help of RiMANGGIS, marketers can have a limited number of segmentations; helping marketers to achieve at least 60% higher response rate on their campaign and saving various costs: search engine cost, segmentation cost and cost marketers need to do multiple channel marketing.

With the adoption of RiMANGGIS, marketers no longer need to spend a huge amount on hiring data mining experts and bother to tell them what they should do, because RiMANGGIS’ 15 million analyzed features of customers can help marketers much faster than having human experts, providing only 300 analyzed features of customers every day or every quarter.