It is almost a tempting, tantalizing retail ability that a retailer dreams to have – turn the ‘gold ore of prospects’ into ‘gold of Happy and Loyal Customers and Brand Evangelists’. That said, striking gold takes painstaking efforts, diligent use of data to achieve the upward spiral of conversion rates. As retailers look to achieve conversions through every possible channel in this omnichannel world, machine learning led conversion analytics guides retailers to make accurate targeting their forte, optimize advertising and marketing efforts, achieve more conversions and increase revenue per prospect-turned customers.
Conquering 3P Conversion Challenges
When an empowered prospect uses the channel of his choice, retailers must be at the Place where the customer is to ensure the prospect-to-buyer conversion rate picks up steam. Apart from keeping the physical as well as the digital doors open to accelerate the conversion drive, retailers must also be there at every point of the prospect journey. Given the proliferation of channels, devices and touchpoints, the prospect journey could well be a long and winding one. Here’s a scenario capturing the prospect journey.
The retailer’s display ad captures a prospect’s eyeballs. It is too good to resist. Curiosity takes over as the prospect lands on a web page of this retailer. Having gleaned required information, the prospect satiates his curiosity further by finding access to review sites. Moving from interest to action, the prospect steps into one of the stores of the retailer to turn into a customer. The pitstops in this journey takes varied shape, as decided by the prospects.
From conquering the channel-agnostic challenge, the retailer moves on to address another critical area – Diligent promotions powered by intelligent campaigns that can capture prospect eyeballs, attention and turn them into buyers. Personalized campaigns then become the key to woo the prospect into buying.
If Place and Promotion are integral part of these prospect-to-buyer conversions, then Price becomes yet another critical feature of the conversion drive. When it comes to pricing, the retailer must know as to how a prospect will react to a specific price point or if the prospect has a price in mind to cut the deal. It is also equally important to maximize revenues from the pricing during this conversion drive.
With machine learning powered conversion analytics, retailers make the most of data to predict customer behaviour and intentions well in advance and leverage prescriptive actions to convert more prospects into buyers.
Giving Machine learning twist to Conversion Optimization
Knowing why a prospect, visitor is lost along the prospect journey is as important as knowing why a prospect has turned into a customer. With robust machine learning models, fed with relevant data, that augment conversion analytics, retailers understand what it takes to bolster conversion optimization.
Leveraging machine learning, retailers benefit from personalized marketing supported by the recommendation engines, behavioural modelling, cross-channel conversion rate and customer path analytics – these become coveted measures to reach out to prospects in a way they create a swell in the loyal customer base – in a way prospects can never refuse to wear the customer badge.
Keeping price as an alluring factor, retailers make good use of price optimization to roll-out real time price that maximizes conversions. Machine learning-led conversion rate optimization also gives retailers the lead to discover profitable channels, measure campaign effectiveness, sharpen campaign strategies, and enhance returns on marketing investments.
At Saksoft, the attention turns to data such as the channel data, social data, profile details, in-store sensors, cameras, log files and browsing history and the most-fitting machine learning model to assist the retailer in the conversion drive. The most telling effect is produced when we take every influencing factor into account, help retailers to increase their conversion rates, sales and revenue while cutting down the costs in achieving the conversion objective.
