VectorScient is a technology company, founded in 2016 and headquartered in Chicago. Using AIIR™, our Data Science platform, and our PredictAlly™ suite of solutions, we provide advanced insights and actionable recommendations to improve business performance.
Online retailers, omnichannel retailers, brands operating in the CPG space, and online panel operators can take advantage of our solutions. Our analytics and predictive recommendations improve marketing, sales, merchandising, and operational performance
Our users fall into 3 categories
- Business analysts across marketing, sales, merchandising, supply chain
- Business executives responsible for P&L, who need to understand the impact of their decisions, review business performance indicators, and develop future actions.
- Data Scientists and power users who need to explore the data or build custom analytics.
No. Our solutions are business-ready. This means, we do all the analysis and generate prescriptive recommendations.
We send the recommendations to the underlying transactional application that you use.
For example, if you are using MailChimp to send marketing emails to your customers, our recommendations are automatically sent to MailChimp. This means, your team does not need to do anything different. Our dashboards are intuitive and throw additional light on various aspects of your business.
Yes. For larger businesses that have internal analytics teams, we provide granular insights. These insights can be used as building blocks by your internal Data Science teams. We do all the heavy lifting in Data Engineering and provide you with ready-to-use analytics. This approach will reduce the complexity, effort, and time of your analytics projects.
Whenever you have a need to precisely target customers with your marketing campaigns. If you are just starting off your startup product(s), you may not have enough customer base to choose from. If you have at least 50,000 customer names in the database and you want to understand each one of them to target only when it matters to each of the customers.
The data owned by you, also known as the First Party data is the most useful and relevant data. Depending on the situation, we also add syndicated data, macroeconomic data to improve the accuracy and relevance of our predictive recommendations.
We take data privacy and security seriously. Our software is compliant with GDPR regulations, which are some of the stringent set of rules regarding data handling. All your data is hosted on a private Google Cloud. All the data is encrypted at rest and in transit. Your data is stored in a place that is private and exclusive to you. Each one of our customers their own database and subdomain. We do not capture any Personally Identifiable Information (PII).
2-years or more is ideal. Given the pandemic events of 2020, data prior to 2020 is recommended. Generally, having at least, the last 12 months data would allow us to see the seasonality and anomalies. We recommend including all the available historical data.
As an online eCommerce business, you will have the first-party customer data related to their purchase history, campaigns sent, customer master details, customer service complaints, etc.
VectorScient’s automated integrators can collect the data from any system via standard APIs wherever possible and universal ETL adopters enable us to collect in non-standard formats like Excel docs, other homegrown systems, or non-API enabled applications as well.
Customer purchase history is the most important data when analyzing to understand your customer. It also helps us analyze the business over the years to understand the big shifts and connect to the product categories as well. Essentially, we recommend that you leverage all the historical data as much as you have access to.
- Customers will have their own individual frequency, patterns, reasons, motivations, interests in purchasing your product.
- Engagement needs to be drawn from each individual customer’s purchases and understand who’s “active” and who has already churned and who’s on the verge of becoming “inactive”. There are many strong indicators that can be analyzed from customers’ purchase history and in some cases, in conjunction with the “campaign history DB”
It depends on the volume of the transactions. Generally, 2 years worth of data is good enough to understand your repeat customers, separate “active” from “inactive”, understand the rate of new conversions versus the strength of existing customers’ remaining future potential to purchase (in terms of $ spend), etc.,
In most cases, the implementations take 3 to 5 weeks. in few cases, depending on the data types and data sources that need to be integrated, it may take longer. In general, if the data source has a published API, the implementation will be quick. For custom and homegrown data sources, the effort will vary.
We provide two types of outputs. The first type of output is our Prescriptive recommendations are directly sent to your transactional applications.
Our strategic dashboards are the second type of output. These dashboards also include advanced insights into your business performance that are deeper, relevant, and precise. These insights help you understand the effectiveness of your strategy. The dashboards also include reports on the effectiveness of VectorScient’s recommendations and the Return on Investment.
Yes. Finally prepared predictive customer lists to target will be automatically uploaded via API integration to your marketing application. The lists will be regularly refreshed as each of your customer’s data changes with every purchase.
No. We are not marketing automation software. Our AI software analyzes each of your customers in your database and their historical purchases along with the historical campaign database. Our product provides you with the likely to purchase customer segments that are ready to campaign from your marketing application software like Mailchimp, Klaviyo, Listrak etc.,
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