“We are in the business of digital marketing and in the past four years have served 445 clients from across the world. After analyzing the client details, I concluded 92% (409) of the clients are entrepreneurs who approached us within twelve months of starting their business. 84% (343) of these business owners operate B2B businesses in the USA, the UK and Australia, and hold an MBA degree.”
Based on the above analysis, I can predict significant sections of our target audience with certain reliability: “MBA holders who have started B2B websites/businesses in the USA, the UK & Australia in the past two years”. I can validate this data by creating two campaigns on LinkedIn. In the first campaign, I set the target audience as stated above while for the second campaign, I set a more generic target audience like Business Owners from the USA, the UK and Australia.
If the first campaign performs better than the second one, my prediction of target audience is true, otherwise, I have to redefine the target audience. In the case of my prediction being true, I will keep refining the target audience as my client base grows and make sure that my campaign is reaching only those who are actively looking to purchase our services.
This is a primitive example of predictive marketing. You use the existing data set of your customers to predict a target audience who intend to purchase your products. Predictive marketing has always been there in one form or another. Traditional marketing campaigns have relied on ‘Customer Segmentation’ to design and implement targeted marketing campaigns. With the advent of advanced technology and the vast amount of data generated on the internet, the customer segmentation has become more accurate.
Earlier, there were few options available like demography, income, location etc. to target campaigns whereas today the targeting options are limited only by the power of your imagination. Some of the newer segmentation techniques are based on interest, behavior, hobbies, online actions, online habits of users. The data science prediction is so advanced that Google can predict what you may be searching for two years down the line. Marketers are using this goldmine to predict their customer base and their purchasing habits more accurately. This phenomenon is known as predictive marketing.
Predictive Marketing Is Based On Science And Modelling Data
Data aggregation
It is a collection and aggregation of data from numerous sources, including internal and external sources. Internal sources could be the existing customer database, leads generated in the past, information about the potential customers with the company, etc. The external sources include potential consumers and consumer segments that are the target base for the products and services. The first step of predictive marketing is getting all this raw data into a single data set for further processing and modelling.
Data analysis
Once the raw data is aggregated, the next step is to analyse it to derive meaningful and insightful information. Unless the data makes sense, it’s of no use. Analysis is the process of isolating the information that truly matters. The generation of information at this stage is necessary for predictive marketing to be successful. Unless you don’t have clearly visible attributes about your markets and potential buyers, you won’t be able to design and predict your marketing outcomes.
Modelling
The vital information which is generated at the second stage is then combined with modelling techniques and algorithms to determine the possible outcomes.
The above three steps define the efficiency of predictive marketing. It can be seen that predictive marketing is totally data driven that uses real facts and figures. Marketers using predictive marketing base their decisions on analysis and modelling of predictive marketing instead of their intuition or past experiences.
There are numerous variables that are likely to impact the outcome of a marketing campaign. Some of these variables existed in the past while the others are new and unprecedented. Predictive Marketing is aggregating and analysing all such variables and then forming a model that is capable of suggesting the possible outcomes, based on which a marketing campaign can be executed.
Hence, the word – “Predictive”. It is a summation of various attributes and variables and a method to analyse their interplay leading to possible outcomes.
What Is NOT Predictive Marketing
Predictive marketing is not telling the future of your marketing campaign by deciding who will and who won’t buy your products. It is not a means to tell you exactly what your sales figures are going to be or what will be the output.
Predictive marketing is not a magic wand and expecting such results from it will only lead to its wrong applications and heightened expectations. It is important to know these limitations in advance so that whenever you plan your marketing campaign and use predictive marketing, you can apply this method in the right manner without falling to the misconceptions about it and later getting disappointed.
4 Benefits Of Predictive Marketing
#1. Better ROI
John Wanamaker is one of the most successful businessmen in the United States and considered by some to be a pioneer in marketing. He once famously said, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half”. The predictive marketing is a step forward to tell marketers which half of their advertising budget is being wasted so that they can plan their marketing budget more efficiently and thus improving ROI.
#2. Better User Experience
As marketers we love advertising our products. However, as a user we hate all kinds of ads. Predictive marketing will help marketers to target their ads to a relevant audience who is looking for their product. So the marriage between ads and consumers will be long lasting and least annoying.
#3. Better Product Development
Currently, entrepreneurs or businesses use gut feeling to understand unmet demands of end users. Date science will help them understand their customers’ needs and wants better and develop products that will be liked by prospective customers.
#4. Better Scalability
Predictive marketing is scalable like other SaaS platforms. You don’t need to install an expensive proprietary software from a vendor and be dependent on them to update the software based on your requirement. Seasonal variation, quick growth of internet based companies can be easily taken care of using predictive marketing tools.
Conclusion
Predictive marketing is a phenomenon that will only get better with time. Businesses that realise its true potential and applications will be far ahead of the competition. In a highly competitive world, with several market players offering similar products and services, the key is to identify the right customers before anyone else and to get to them first.
Predictive marketing makes it possible for marketers to develop a model based on concrete quantitative data to generate knowledge about the markets and consumers, and their behavior. With the right application, predictive marketing is capable of significantly reducing costs, making marketing campaigns more precise and effective, and increasing the output.
Do you use predictive marketing?
Image: Author’s Own
