Role of Predictive Analytics
Predictive Analytics is a very new domain when it comes to the field of online marketing and e-commerce. Some online players still consider it complex, something, which is difficult to sell to the executives considering, a huge investment it requires in terms of hardware, statistical tools, and most importantly, the right people in-house. On the contrary, we have online players, who have realized the potential of this concept, and have already started investing in this area either, by building their in-house team of Predictive Analytics or, outsourcing to a team of experts offering automated predictive solutions. With markets becoming more competitive by the day, data size exploding, and ‘big data’ concepts becoming increasingly important, the role of predictive analytics in selecting the right set of information, identifying the underlying hidden patterns, and providing in-depth actionable insights is becoming indispensable to sustain and be equally competitive in the industry. But, Predictive Analytics-driven recommendations are incomplete in isolation, because even the best of insights may go unheeded if, the right people in the company are not approached. Here at Nabler, we have experienced that, even the VP of Digital Marketing needs support from the Senior Executives by presenting a solid business case for investment before, he/she teams up with Sales, IT, and their Support Desk. Being a VP of Digital Marketing, you can choose the Predictive Analytics technology, vendor or solution, but when it comes to big data, it’s about collaboration and data sharing.
Challenges faced by a VP of digital marketing
Being a VP of a Digital Marketing, you have your daily platter full of operational and strategic challenges, and to overcome those challenges, you need reliable data insights to make smart and calculated decisions. At the end of the day, you are responsible for boosting the annual sales, achieving an aggressive online growth rate, keeping the cost per acquisition under control, boosting the channel ROI, and most importantly, a knack for predicting the future based on historical data, and come up with smart campaign and targeting strategy, which generates decent ROI by keeping the cost per acquisition under control.
Here at Nabler, we have worked on various Predictive Analytics projects for our clients, and in all these projects, we worked very closely with VP of Digital Marketing, VP of Sales, and VP of Merchandising, but despite working with these roles, we always felt a void at client’s place. Based on our experience in this industry, having an in-house person to champion your Predictive Analytics projects is vital if, you’re to gain a measurable return on investment.
The another major challenge the VP of Digital Marketing faces is, having accessible, historical data in the right format for their Predictive Analytics team. Based on our experience, whatever predictive analytics tools, third-party consultant or in-house staff member you employ to do the predicting for you, they will require data and snapshots of customers and information at various points in time if, they are to learn how to predict.
“Predictive analytics is never going to solve bad hygiene in sales processes and product marketing,” the VP’s and CMOs need to have a deep comprehension of how predictive analytics works at least in principle if, they’re going to get significant returns. “You have to be clear on what your targets are, your pain points, and your value proposition.”
Predictive Analytics to the Rescue
Let us take some scenarios where, predictive analytics can be a blessing.
When there are several channels for promotions and sales, it can be a daunting task of determining, which one to give priority, in such cases, analyzes like attribution modeling and channel budget allocation can be very helpful. The former helps understand which channels perform better while, the latter helps in allocating budget to the channels based on an ROI calculation, hence helping to identify the most effective channels to leverage revenue.
Sentiment analysis, a very new concept, is yet another powerful method that captures the positive and negative sentiments of your consumers, and allows you to gauge the image or perception about your brand in the customers’ mindset, which is essential to maintain continued loyalty towards your brand and keep the attrition rate under control. The analysis involves, social listening and advanced methods of text mining, integrating feedbacks from areas of customer reviews to social media discussions. As an example, the analysis can identify, vendors consistently underperforming and gives the opportunity to be acted upon, hence helping the company maintain the critical edge to survive healthier in this competitive landscape.
Other areas where predictive methods can be beneficial are forecasting the expected sales to plan for inventory management, incurring investments and fixing issues beforehand.
Let us share with you some few interesting problems we solved for our clients by leveraging Predictive Analytics concepts:
Improve Revenue Generation:
This project was done for one of the biggest players in the eyewear industry in North America. The objective was to be able to highlight certain brands, which when marketed in specific US states would yield them a significant improvement in revenue. For e.g. generating additional sales for Prada brand in New York, California, and Connecticut.
How our analysis helped in improved decision making?
(a) A significant marketing budget was saved as, every state need not be targeted with every brand
(b) Exact list of target brands and states statistically guaranteeing increase in revenue generation
(c) With spend data an expected ROI to plan out how much exactly to spend on brand promotions
Improve Conversion Rates/Increasing Order Value:
This analysis was done for a large home improvement retail chain in North America market. The VP of Merchandising working with this retailer approached Nabler to identify, the key products and categories that should be promoted on their website during the upcoming Black Friday and Cyber Monday event in 2013.
(a) An exhaustive list of products that needed promotions to meet the target revenue was provided
(b) An estimated number of product views for each promoted product was provided for optimum visibility
(c) For every additional product view the incremental return was computed thus helping to plan the spend
(d) Finally, the expected profits that can be generated was quantified
Improve Qualified Leads:
This analysis was done for a services outsourcing company in Asia Pacific. The objective was to guide the visitors along the path that had the greater chances of getting the visitor converted and thus increase qualified leads. The click-stream data coming from the Google Analytics solution was studied to understand, which pages assisted the most in conversion, what is the weighted conversion potential of a page, how deep the visitors are navigating the store taxonomy, and most importantly, what are their exit and abandonment points. Based on this analysis, the recommendations were made.
How did the analysis lead to improved decision making?
(a) A list of URLs were suggested to be placed on the home page/blogs which when placed would improve the conversion, i.e. guided conversion
(b) The expected lift from the recommendations suggested, i.e. an estimated ROI from the changes was provided
(c) A test and target exercise to quantify the recommended URLs actually increased traffic and lead to conversion were carried out
At the end, we want to conclude this discussion by requesting all those VP of Digital Marketing working with small to mid-size to large online retailers and brands, to remember an important fact that, the predictive analytics is only useful if, you act on the information generated. Both VPs and CMOs need to build a plan for what is going to be predicted and what they are trying to achieve. In addition, they must look at how best to give the results of their predictive marketing efforts to the sales, merchandising and senior executive teams.
“Being a VP of Digital Marketing, you have to flesh out what the business value is going to be, and how to act on that prediction, or you’re just putting the cart before the horse,” As a marketing chief, you must do whatever it takes to make that operational change.”
If you’re not 100 percent clear on what the output will look like and aren’t willing to incentivize behavior in the sales organization or marketing team, it’s not worth making the investment
To learn more about Nabler Predictive Analytics capabilities, visit our website and contact our Business Development Representative to arrange a one-on-one call with our Predictive Analytics Consultant. Happy Holidays!!