Multi-Lingual Patent Pending Machine Learning / NLP for real-time Consumer Purchase Journeys
Increasingly the consumer is calling the shots in retail. They meander and hop through multiple digital channels on their path to purchase. They engage with a brand numerous times prior to making an actual purchase decision.
In a recent survey by RSR Research retailers were asked to name their top 3 challenges – No.2 with 56% response was the need to understand the path to purchase. The complexity of the path presents very difficult challenges for marketers and brands to overcome. In fact the more you think about it the complexity increases exponentially?
Lets take an example process and try and map it?
Purchasing a car – one of the typically most expensive purchases made by an individual or family. It is usually one of those decisions that takes time; unless the consumer is one of those people who always buys the same model and brand!!
So how do we go about mapping the path to purchase? What information sources are available? Comparison websites, consumer review sites, Facebook, Twitter, friends, family – oh and the old traditional route of popping into a car dealership and getting hassled for weeks afterwards on our decision by that salesman desperate to hit his month end number!!
So lets pick a few random demographic person types?
- Male – married – 45. Seeking new family car. Technologically savvy. Reviews some websites, speaks to his family and friends. Pops into his local dealership. Looks for the best deals around, has a quick scan on social websites. He may take a month or 6 and then suddenly makes a decision and walks in to buy.
- Male – Widower – 68. Seeking a new reliable car. No interaction on the web or social. Pops into local dealership he always buys from. Makes his purchase. Decision took a month.
- Female – Single – 28. Young professional. Seeking a sports car. Asks her friends on social media, reviews comparison sites. Does lots of research. Calls up and buys via a car lease broker. Researched for 3 months, bought in 1 day.
In just 3 (simple!) examples the path to purchase is very different; and for each of these demographics the path to purchase is going to be very different based on a massive range of factors. Therefore the exercise of mapping out the path to purchase is going to be incredibly complex. Let alone attempting to think about some differentiation in the path based on the type, value of the vehicle a brand is attempting to sell. And this is just cars?? It gets even more complex with goods of lesser value and more instinctive purchase profile.
So why not approach it another way? Focus on finding pre-purchase intent across all forms of online interaction and devise responses that match the expression of purchase intent. At Chatterbox Labs our Path 2 Purchase product identifies 3 classifications of pre-purchase intent:
Interested? – send them an offer for test drive / information on a deal
Considering? – Send information to sway the decision process
Lead validation? – close the deal, send them information of local dealer or how to buy today
With machine learning Path 2 Purchase you don’t need to map out the consumer path to purchase. You need to map out the ACTION you will take on the data we find for you in real time automatically. You map the ACTION you take to drive the consumer down a path to purchase of your product! Irrespective of buyer profile and theoretical journey you can capture pre-purchase intent and take action driving new sales and revenue to your bottom line.
And that’s not all – we also find post purchase information in social data. So what?
Well a few examples we have thought of and depending what you are selling I am sure you could find more.
- Customer makes a purchase and expresses dissatisfaction; get your customer service team to engage quickly and appropriately
- Customer makes a purchase and expresses how happy they are; engage with them and turn them into even stronger advocates; highlight the post on your own website
- Customer makes a purchase and tells 5 friends about what a great experience they had; contact those 5 friends with a deal / information to drive them down your path to purchase.
Turn your path to purchase journey around from trying to predict to actually finding ACTIONABLE data across the globe in real time with ‘Path 2 Purchase’ from Chatterbox Labs. For more information please contact Andrew Watson, VP Strategic Alliances – Andrew@chatterbox.co or visit our website for more information www.chatterbox.co