Vestorly and the Application of Machine Learning to Personalized Content
Stop us if you’ve heard this one before, your company has a mountain of data that is sitting around like an untapped resource. You wish that there was some way to unlock the value of this hard won stockpile of unformed insights? Unless you’re at an industry leading marketing or advertising firm, the aforementioned challenge probably hits home.
Professional service providers, particularly those in the financial services industry, often collect reams of data on brokers, agents, reps, etc. only to let it sit in the database with no way of using it to identify broader trends. Professional service providers need to provide personalized experiences for their clients, applying the scalable techniques of modern media platforms or risk being disintermediated or becoming the next travel agent. Only within the last few years has the wealth management industry realized this vulnerability and how not personalizing and applying data-driven techniques for marketing and client engagement will result in lost revenue, longer sales cycles, and increased operating costs.
Artificial intelligence is a hot topic in many verticals these days and professional services is no different. While AI is by and large a slick buzzword without any definite meaning, what is a reality in the current era is machine learning and the benefits that come with being able to get the right content to the right audience member at the right time. That is the core mission of Vestorly and what we strive to provide our clients and their audience members.
Currently, Vestorly is able to target content sections to a client’s contacts. Each time an email is delivered to a customer’s contact, an experiment is run to test which type of content gets traction with that specific person. Over time, as more and more of these experiments produce data points that are fed back into Vestorly’s content engine, our customers’ contacts receive better and better targeted categories that increase engagement which in turn accelerates the precision of Vestorly’s content recommendations to that contact.
In the near future, Vestorly will be able to not only learn what categories of content a customer’s individual contacts prefer, but also what specific articles are most appropriate to send to them. The experiments that get run during each email delivery will at that point test for engagement per article per content section that will target the recipient with specific articles tailored to their past views. At this point, Vestorly will have emails that deliver articles specifically chosen for each email recipient.
Additionally, when a Vestorly customer curates their custom feeds of content via thumbing, this feedback will help to personalize that custom feed to their tastes and what kind of content they wish to distribute to their customers. Thus, the customer will be able to personalize a custom feed of content so that the pool of content available with which to run the aforementioned experiments at the point of email send is personalized to the sender. The articles that will be chosen from that pool will then be personalized to the customer’s client.
Only through the scalability that machine learning offers professional service firms with large audiences can such providers reach each individual as if one took the time to personally curate the content being sent to their customers. One-size-fits-all content experiences guarantee that you lose your customers’ attention. Stop this attrition today and find out how Vestorly can plug into your current work flow.