FeedStock
The modern, mobile enterprise will be defined by its ability to capture and utilise data.
“Any tool that can pull together data from various sources in visually enlightening ways puts a business ahead of others immediately.*”
Over the past 12 months, FeedStock has conducted conversations with C-Suite executives from across the financial services, consulting, pharmaceutical and real estate industries to identify and address the potential benefits which enterprises can unlock if they pursue data-driven business practices. In this white paper we divide these potential benefits into three categories: driving revenue growth through empowering “knowledge workers” with data-driven insights; improving front-office productivity through automating non-core administrative tasks; and AI technologies to minimise the cost, risk and burden of regulatory compliance. By combining the results of these conversations with the findings contained in our dataset, we deliver statistics and expert opinion on the power which smart use of data has in revolutionising an enterprise’s revenue generation.
Smart use of data enables sales professionals to better understand client preferences and behaviour and visualise opportunities and risks within their existing client base. Armed with the correct data, managers can refine and optimise the customer experience and deliver tailored, timely and relevant information. In today’s workplace environment where the average buy-side investment manager reads only 20% of their emails per day, it is more important than ever to cut through the noise to deliver the level of service that is expected.
Sales executives spend as little as one-third of their time performing sales activities; 64% of their time is spent doing non-revenue generating administrative tasks or inside sales research.* Artificial intelligence technologies have enabled the automation of many of these administrative tasks and not only free up a lot more front-office sales time, they also result in a complete, accurate and impartial data set on which to base enterprise decisions. The highest performing sales teams are 1.5 times more likely to base sales forecasts on data-driven insights rather than intuition.* Getting ahead in today’s high-frequency, multi-channel sales environment requires the deployment of data-driven practices.
(Source: Forbes Insights, Survey of 720 sales representatives, 2018)
(Source: Salesforce, 26 Sales Statistics that prove Sales is Changing, January 2019)
The regulatory environment is increasingly stringent and costly to implement. It has been estimated that in the investment banking industry, 40% of an enterprise’s costs are compliance related.* In asset management, the cost of MiFID II compliance is forecast to rise to 10% of revenues by 2021.* Last year, the automation of research inducement monitoring proved to reduce one of our client’s risk of inducement by over 90% and the evidence provided by research consumption data exactly reflected the result of the firm’s broker voting system. This is a clear example of how artificial intelligence can not only minimise compliance costs but also streamline processes to enable front-office employees to spend more time doing what they do best: generating revenue.
(Source: EY, Building the investment bank of the future, 2016)
(Source: Duff & Phelps, Global Regulatory Outlook, December 2018)
Bespoke emails are more than 25% more likely to be replied to than generic emails.
The trend of increasing mobile email open rates has slowed down. 65% of all email opens and reads are done on desktop.
8am – 9am GMT and 9am – 10am EST are the time windows in which the most email read/open activity is recorded in the capital markets industry.
Only 12.75% of the average B2B sales professional’s outbound emails are read but an email which is bespoke to the recipient and opened in the first 60 minutes of having been received is 46% more likely to generate a reply.
Understanding individual client behaviour and interests is the key to delivering the required quality of service and reducing client churn in today’s workplace. The growing number of channels, devices and mediums with which we communicate has made it increasingly difficult to synthesize and streamline the sales process, yet this is integral to building and maintaining healthy client relationships. Over the past two years, the implementation of data analytics has been proven to increase the speed of initiation of first sales by 50%, reduce churn by 25%, increase sales from new accounts by 10% and improve return on sales through pricing by 2 – 5%.*
(Source: McKinsey & Company, The five lessons B2B sales leaders should learn to make analytics work, December 2019)
Using the latest artificial intelligence and deep learning technologies to unlock hidden insights from within an enterprise’s client engagement data is essential for organisations who are committed to empowering their workforce with the tools they need to capitalise in today’s environment. A complete, accurate and impartial data set allows the knowledge worker to visualise opportunities and risks within their client base and make better enterprise decisions.*
(Source: Forrester, Extending the value of AI to the Knowledge Worker, January 2019)
(Source: FeedStock, Data on email user behaviour, 01.01.2019 – 01.01.2020)
This FeedStock article We’ve previously explained the importance of making sense of the unstructured data generated by an enterprise’s communication streams to capitalise in this increasingly competitive sales environment. Holistic data visualisation can lead to some crucial, revenue-generating discoveries. Any tool that can pull together data from various sources in visually enlightening ways puts a business ahead of others immediately.*
(Source: Forbes Insights, Everyday AI: Harnessing Artificial Intelligence to Empower the Knowledge Worker, January 2019)
The average sales professional has an email read/open rate of 12.75% but the chances of the email being engaged with increases by over 40% if it is tailored to the recipient and sent at the correct time.* The ability to build and maintain successful client relationships is significantly improved by the intelligent use of real-time engagement data to guide the content, timeliness and format of the information.
(Source: FeedStock, Data on email user behaviour, 01.01.2019 – 31.12.2019)
An automated data-capture system collects 10x more client engagement data than a market leading CRM.
14 hours per week per sales person is spent on manual CRM data entry.
High-performing sales teams are more than 1.5 times more likely to base forecasts on data-driven insights rather than intuition.
According to a Forbes Insights study conducted last year, 64% of a sales representative’s time is spent doing desk research and non revenue-generating tasks.
A recent study done by Forbes of 720 sales reps found that nearly two-thirds of a sales professional’s time is spent doing non revenue-generating activities. The impacts of manual CRM inputs on productivity are supported by a Salesforce statistic which found that 91% of CRM data is incomplete and 70% of client data becomes obsolete within one year.
Removing the need for manual data entry not only frees up more of a sales professionals’ time, it also results in a complete, accurate and impartial data set on which to base enterprise decisions. High-performing sales teams (the top 24% of more than 2,900 sales professionals surveyed) are 1.5 times more likely to base forecasts on data-driven insights. Conversely, under-performing sales teams are 1.7 times more likely to forecast on intuition.*
(Source: Salesforce, 26 Sales Statistics that prove Sales is Changing, January 2019)
“Almost 10x more client data captured than our CRM system with zero disruption. Both parts of the business win.
An automated approach to understanding client interactions has resulted in amazing insights.”
The cost of MiFID II compliance is forecast to rise to 10% of a firm's total revenues by 2021.
AI technologies have proven to reduce a firm's risk of MiFID II inducement by over 90%.
As much as 70% of compliance costs can be reduced through technology.
Increasing pressure on the bottom line and a constantly changing political and regulatory environment are making it increasingly important for organisations to lay the foundations of a future-proofed, compliant enterprise. With the cost of MiFID II compliance set to rise to 10% of revenues by the end of 2021* and compliance costs amounting to as much as 40% of a firm’s total costs in today’s environment,* it is unsurprising that the RegTech industry is set to grow by 25% year-on-year to a forecasted $4.9bn in annual revenues by 2023.*
(Source: Duff & Phelps, Global Regulatory Outlook, December 2018)
(Source: EY, Building the investment bank of the future, 2016)
(Source: The Cambridge Centre for Alternative Finance, The Global RegTech Industry Benchmark Report, 2019)
“Technology change can bring opportunities for innovation and lower costs […] We will look at ways to reduce the burden of regulation through the use of technology in regulation – RegTech.”
Investment in RegTech lays the foundations for a data-driven enterprise. Superior data drives superior enterprise decisions. Using AI technologies to provide a complete, accurate and impartial data set will enable business managers and executives to gain a full understanding of enterprise operations. 78% of senior executives see AI driving a high degree of performance improvement across their overall business. AI will have most benefits in eliminating repetitive processes (51%); streamlining decision making process by providing relevant information (33%) and delivering new insights (31%).*
(Source: Forbes Insights, Everyday AI: Harnessing Artificial Intelligence to Empower the Knowledge Worker, January 2019)
