Predictive Analytics: The Future of Digital Marketing
“Harry: Professor Trelawney?
Professor Trelawney: He will return tonight! He who betrayed his friends – whose heart rots with murder! Innocent blood shall be shed and servant and master shall be reunited once moooooooore!
Professor Trelawney: Oh, I’m sorry, dear. Did you say something?”
Predictions have always fascinated the human minds. Be it Trelawney, Oogway, Sir Nighteye, or Xaviers – seeing the future has always made them invaluable to their surrounding people. The fascination breaches the fictional realm and enters the world of reality. After all who wouldn’t!
The digital world too seems captivated by this, and hence, comes the scope of Predictive Analytics. Let’s say, the Digital Marketing world is getting its high from this new scope that is helping them venture into the future. While digital marketing is already enjoying their newly created fandom over innovative online marketing opportunities during the pandemic times, predictive analysis is only chiseling its efficiency.
But wait, how can we start talking about what predictive analytics holds for future marketing, without first acknowledging what it is? What are you waiting for then? C’mon!
Predictive Analytics – What’s That?
The advertising and marketing industry has crossed the 7 seas in an attempt to acknowledge and fathom out the minds of prospective buyers and consumers. However, there has been a prominent hurdle – they had no Professor Trelawney on their team to predict the future.
Then again, it seems that now, the industry has its hands on such a professor, a.k.a. Predictive Analytics – its technologies! The emergence and its propagation have led to convenient access to predict client behavior in advance. So, the future is here for digital marketing!
As per predictions, the predictive Analytics world is looking at a global market reach of $10.95 billion by 2022. The subset of predictive analytics, that is, predictive advertising is often utilized by enterprises to understand client behavior in advance. In this case, the analysis is used to think upon the future emerging trends and accordingly optimize the sales and marketing approaches.
This 2nd stage of business analytics is a branch of advanced analytics that is often used with algorithms to predict future outcomes. So, how to dip your ankles into Predictive Analytics? Let’s offer you a helping hand here!
Steps To Get Grooving With The Predictive Analytics Process
Do you know the hush-hush secret of Predictive Analytics? Here’s spilling some beans on it – it analyzes patterns based on the transactional and historical data that can, later on, be processed in order to spot future scopes and/or risks.
For those who have already caught up with why they should be catching up with predictive analytics to get their digital marketing technique, future-ready, here are the steps. Carry on!
Step 1: Define Outcomes
Think of the business question that you would want your data to answer. Make sure that the outcome is well-aligned with your business vertical.
Step 2: Collection Of Data
Draw out a roadmap for the data that will be acquired. You can also list out the plannings to collect such data, and how you would be organizing it because after all, you will be dealing with a huge quantity of data.
Step 3: Analyzing Data
Now inspect the data that you have collected and scan if you have your required list of useful information. The next step would be to draw out the conclusions about your targeted clients.
Step 4: Statistics
By now you will have a lot of conclusions in your hand. This is the time to test the same.
Step 5: Modeling
This is the major step for Predictive Analytics. In this, you will be creating multiple predictions about the future behavior of your prospective clients.
Step 6: Deployment
The collected data will now be utilized to frame marketing strategies and implement suitable tactics.
Step 7: Monitoring of model
It’s time to track the steps and report the same. This will have a severe impact on the effectiveness of the campaigns that are predictive data-driven.
Go Predictive For Trending With The Future Of Digital Marketing
Nature can still boast of its unpredictive nature, considering how it brought on Coronavirus and the next in the queue, the Bubonic plague. Then again, it seems like the digital world has escaped this possibility and got in a Seer of its own. Is this the only scope for Predictive Analytics? Nada! There’s a lot more to this. Read to know about some such… (Remember we said, ‘some’, there are many more!) –
Digging Up The Treasure Trove Of Big Data
AI is in town! Imagine the hype to be similar to the World Cup for your preferred sports, only in the digital world. While it brought with it the scope of Predictive Analytics, there is also Big Data in the scene. This treasure trove of data, coupled with Internet Of Things (IoT) for data analysis and collection, brings in a plethora of leverages in the backdrop of consumer insights. This includes –
- Behavioral and demographic audience data
- Performance data and competitor strategies
- 3rd party intent behavior-based data that is collected from diverse platforms on the web.
This treasure trove of data helps marketers get a hold over the preferences, intentions, and purchase patterns of each client, individually. The data also guides them in tracking the market nuances that they are putting their foot in.
Acknowledge The Product Fit
Acknowledging the historical purchases, lead, and behavior data, enterprises have the ability to fathom out the precise requirements and needs of clients. This translates into developing future merchandise to meet with the requirements or enhancements for the current products that fail to meet the sales targets.
Bull’s Eyes – Relevant Audience
With an internal audience and 3rd party behavioral data, marketers are able to spot the best possible prospective clients that they need to target via their campaigns. The narrowed down approach makes it feasible to broaden the audience base even further as compared to regular marketing targeting tactics via the drawing of correlations between behavioral and demographic factors. Such technologies are further elevated by –
- Facebook Similar Audiences
- Google’s Lookalike Audience
While you (sans your Digital Seer) might be relying only on the first party metrics based on behavioral patterns, like – lead magnets downloaded, visited site pages, and carts abandoned; it limits your knowledge.
Optimization Is In Town –
- Ad Copy
Understanding client behavior has a positive impact on businesses and aids them to create targeted and relevant converting ad copies. 1st and 3rd party audiences are brought in to build buyer personas that are robust. With machine learning, predictive insights are used and convert smart choices into enhanced ad designs and advertising copies. The marketing collateral is optimized for the effectual target audience.
- Ad Spend
Reaching out to the wrong audience leads to a considerable waste of marketing expenses. Businesses need to focus on mitigating wastage of as spends to draw the dual leverages of – channelize the saving of budgets, and invest the same in other marketing initiatives. Predictive Analytics can be of help here via executing targeting and bidding adjustments in real-time to ensure more ROI drives.
Shoot At Micro-Moments
Your smartphones are a pestering presence for advertisers, did you know that? They have a tough time targeting the audience at relevant times. Subsequently, by the time, consumers look into the advertisements of some products, let’s say that the ‘ship has long sailed’.
With you being social media savvy, micro-moments are something you are well-acquainted with. For digital marketers, this is a golden opportunity. However, it requires some automation. In this regard, Predictive Analytics is the best way out because they can analyze consumer requirements owing to it being equipped to handle the colossal amounts of data in real-time. With machine learning, marketers can have their hands on intent from the locations, search queries, and multiple other such factors. And all of this happens in the backdrop due to which marketers have the liberty to pursue other scopes in media-buying.
Convenient Access To Lifetime Value Prediction
The relationship between the brand and the client is crucial enough to keep a track of the client data. This Customer Lifetime Value (CLV) is well tracked by predictive analysis with which one can grasp the historical data of clients and can use the same to predict the future lifespan of clients, individually. It also catches up on the revenue that the relationship fetches. It can help marketers set the budgets for the acquisition of clients, thereby offering a precise and predictive ROI.
Go For Apt Influencers
Once upon a time, social media influencers could easily grab on a thousand followers. But as time rolled on, marketers got picky when choosing influencers as they put in metrics to make informed decisions when relating products to the perfect influencer.
However, the mystery associated with the influencer-output becomes too much of an adrenaline rush for organizations. Predictive Analytics comes as the respite here by –
- Confirming how the chosen influencer performed across time.
- Evaluating the quality of the posts by influencers and the engagements on diverse platforms.
- Determining which audiences or age groups respond the best to an influencer’s posts.
Venturing Into 2020 & Beyond
Companies in the energy, transportation, agriculture, and manufacturing industries have already come to conclude that Predictive Analytics is going to be their future. An approximate of 83% of enterprises (globally) is investing significantly in big data projects.
While companies continue to embrace Predictive Analytics, it is time that digital marketers also accept their fate, ease their journey, and make their efforts easier.
So, where are you amongst the predictions and fortune-telling? Still, shying away from your professor Trelawney?
Pratip Biswas is the Founder and CEO of Unified Infotech, a New York-based web design company that has been featured in Deloitte Fast 500 | Fastest growing tech companies in 2018. His company is working with Enterprises, SMB’s and Start-ups to improve their efficiency through Digital Adoption and help them discover new possibilities through constant innovations. Pratip also writes regularly on Blockchain technology and has been published in publications like “Yourstory”, “Dzone” etc.