Remember when the world went gaga over Amazon’s decision to ship items before they are even ordered? Oh, and they even have a patent for what it is called – anticipatory shipping! There’s no doubt that the move to expedite the shipping process by the Seattle-based e-retailer is pure genius.
By how does Amazon plan to determine what the customers are looking for?
Through their buying patterns, demographic data, browsing habits, etc. In simpler words, they plan to put the Big Data together to predict customers’ preferences and needs.
This concept also goes by the name of “predictive analytics” which is defined as the use of data, statistical algorithms and machine-learning techniques to provide an assessment of what will happen in the future.
A report by TDWI in 2013 revealed that the power of predictive analytics is applied to:
- Identify trends
- Understand customer behaviour
- Optimize marketing focus and spend
- Improve business performance
- Promote cross-sell opportunities
Though the concept has been around for years, the use of predictive analytics has tripled since 2009, according to an Accenture survey. That is largely due to the advent of Big Data, and not to mention the accelerating technological innovations.
Today, marketers across all fields are more interested to predict tomorrow than explain yesterday.
Think Like The Buyers
It is understood that predictive analytics allows the process of gaining insight about the customers’ preferences. The process kicks out any scope of “guessing” what they may like, whatsoever.
Companies can focus on tailoring the message and communication as per the customers. By optimizing buyer personas, discovering their pain points becomes easier. This enables the marketing strategies to be centered around their needs.
Identify Customers Who Have A Propensity To Leave
Not all customers have a consistent experience with a brand. Sooner or later, they leave. The only differentiating factor is “how soon do they leave?”. With predictive analytics, a lot more personalized experiences can be created to keep the relationship alive and kicking.
With the use of predictive customer intelligence, a churn model can be created by the company to attain quantifiable metrics in order to fight in favour of the retention efforts.
Generate Leads That Convert
Data collated by the digital footprints that potential buyers leave while conducting market research can be leveraged in sales process to increase conversion rates. In a B2B framework, especially, this data predicts the desirability to buy a product (or service) with more than 85% accuracy.
By using the information provided through predictive intelligence, marketers have been recorded to reduce the cost of acquiring quality leads by almost 20%!
This optimizes selling efforts and time by allowing the sales rep to focus on only those prospects with whom the chances of closing the deal are high.
Make Sense Of Business Data
With the reducing prices of clouds storage, companies are collecting data faster than ever. On top of it, they don’t use more than 1% of the stored data for taking business decisions.
So, what happens to rest 99%? Nothing.
That is because companies are not able to make head or tail out of the unused data. In order to scale up, they need to be able to retrieve that information. With the help of predictive analytics tools, this data can be sliced and diced and put to some good use.
Create Accurate Revenue Forecasts
Companies often take drastic business decisions on the basis of rough revenue models – which might not necessarily consider the fact that revenues fluctuate and industry is dynamic in nature.
With predictive analytics, uncertainty in sales and mechanisms through which companies generate revenue can be accounted for. This way, companies get a more practical forecast report to base their decisions on – which also gives transparency and variability of both positive and negative revenue outcomes.
Drive Focused Marketing Strategies
When the companies know where there buyers are coming from, it becomes easier to focus marketing spends. Decisions on improving direct email results, events to participate in and content syndication providers (email, social media, blogs, etc.) to name a few can be taken smoothly.
Moreover, such an organized manner of working saves time and money of everyone across departments in an organization. Which company wouldn’t want to optimize its efforts?
Predictive analytics has the power to encourage marketers perform even better at what they do and to focus where the buyers are. With the smart use of predictive intelligence, they can justify their marketing investments by enhancing engagement.
They can not only generate high converting leads but also attract and retain more customers, just by studying their behavioural and demographic patterns. In simpler words, predictive analytics makes it easier for the companies to not only do their business but also excel in it!
Do you think predictive analytics offers something that marketers from both B2B and B2C industries must use? Or do you think this concept hampers the way they communicate their value propositions to their target market?