Marketing & Sales Analytics
In Big Data and Machine Learning
EMPLOY AI AND BIG DATA FOR AUDIENCE ATTRACTION AND RETURN ON AD EXPENSES
Big data and AI is the most effective strategy for marketers and sales since the Internet entered the buisness world around two decades ago
But what are the REAL Challenges of Marketers to understand it's functioning?
For the Modern Marketer
The need of the hour is Artificial Intelligence (AI) in order to grow and automate efficiently all marketing strategies.
Transparency - This is the process to figure out not only why a MODEL selected a customer in it's next marketing campaign, but also concrete reasons behind it for doing so.This helps to reach out to each customer with the most appropriate message in order to optimize effective marketing.
Easily scale market size- In modern times it's extremely difficult to track millions of customers effectively. But with SPARKFLOWS marketers can very easily process huge data to reach out to the details of every customer and hence make any buisness profitable.
Quick action to Marketing - To sustain in the run of modern marketing, your PREDICTIVE MODELS need to be updated with latest trends. This is because human behaviour is continuously changing. SPARKFLOWS is capable of creating such predictive models in no time to update results as soon as required.
Accuracy - " Cluster Analysis" is no longer a good marketing policy because today's consumers prefer to be treated as individuals rather as a group. Clustering is now a descending trend due to reduced sales, high cost and non- fashionable style of marketing. This has been replaced by the modern ML marketing techniques which is capable of accurately predicting the complex human behaviour of an individual.
For the modern Marketer
Pricing analytics involves analyzing price sensitivity in market segments and is especially useful in highly competitive markets where everything that can be done has been done.
Pricing analytics requires data mining and the development of forecasting models and algorithms. It also often involves multiple, concurrent business experiments that can be run quickly and easily so you can measure what is likely to happen with each price change.
If you use pricing analytics to improve revenue, it's important to remember to improve the value you give to customers who are willing to pay more.
Competitor analytics is important for marketing and strategic planning to understand their strengths and weaknesses and identify opportunities to exploit and threats to navigate.
There are different ways of gathering competitor data, such as business journals and newspapers, annual reports, product brochures and marketing activity. You could even have an employee, friend or family member to buy a product or service from your key competitors and assess their experience.
The most useful tip for competitor analytics is to do it but practically most don't.
NON CUSTOMER ANALYTICS
Non-customer analytics is the understanding of people who are currently not your customers and what they think about your product, services or brand. By identifying who is not buying from you and their reason for doing so, you can expand your market to include those individuals.
If you want to know why people are not buying your product or service, you need to ask them: interviews, questionnaires and focus groups can help.
It can be remarkably easy to get feedback from people who are not your customers using the power of social media.