Sell-side research providers have seen their market change dramatically over the past few years, even for those outside the MiFID II jurisdiction. Everyone is facing new and different expectations from clients and the squeeze of reduced or dispersed research budgets. But for many research providers the tools and resources they need to survive and thrive are well within reach – in fact they may have them already, it’s simply a question of making them work. Here are three key mistakes I see sell-side research providers making, and how to fix them.
Not embracing new tools
When it comes to research, many providers have stuck with what they’ve always been doing. Two obvious examples are the continuing dominance of email and PDF as key tools for research distribution.
It’s clear that many busy buy side professionals are receiving completely unmanageable levels of email and much of it is deleted unopened. Similarly, 80% of research is still distributed as PDF, even though we know most PDFs aren't read.
This is a great shame as there are countless formats research providers can try, from audio and video to interactive HTML and data. If your clients aren’t interacting with your research, try something different! Clients are increasingly looking for highly bespoke research products and services, and there are more than enough ways to deliver.
It’s not just research formats where sell side firms are missing out on exciting new tools. A recent Singletrack survey of sell-side firms revealed that more than half don’t currently use AI/machine learning to support their business, and even more shockingly, have no plans to in the future!
Advanced analytics can be transformative, particularly for sell-side firms and IRPs seeking to progress in their digital transformation by helping make sense of huge amounts of information which would be almost impossible to process manually. For example, an AI based tool can suggest the best time to call your key contacts, by ‘learning’ when they’re likely to answer the phone and prompting you to get in touch at that time.
With the potential for such great benefits with AI and machine learning, reluctance to embrace such a powerful tool is a tremendous loss: I would go so far as to say that this indicates more than half of sell-side firms and IRPs don’t really want to be successful.
Deep down, I think we all know that varying distribution techniques and using AI to analyse data, pick up potential problems or even suggest follow up actions will allow us to better service clients and increase traction. But adoption is lagging. By taking up these opportunities, firms can improve their reach, optimise their provision, and get an edge on competitors.
Not using the data you already have
On the surface, many research providers seem ready to tailor research and distribution to clients and create valuable, bespoke experiences for them … but are they really? They all say that they already know what the clients want but stop short of really diving down the rabbit hole to prove it.
For example, sell--side research providers end up with a huge amount of information about their clients. There are analyst meeting records, call logs, readership stats, downloads, email opens, and more. Then there’s the feedback the buy-side provides: payment structure, broker votes and direct feedback. They work hard to gather all this data (I can expound on how using good systems can save much of this work - but let’s leave that for another post) but only put a minimal amount of effort into analyzing it. I don’t want to dismiss anyone’s efforts here, but hard work doesn’t always give you the best results, especially when you have advanced analytics systems that can easily do it faster, easier and better.
Missing the details
But what to do with this information? Most research providers will have the basics: they know who spends the most and who spends the least. But what about finding the average payer who will spend big for a particular topic or event? What about looking in detail at the changing dynamics of rising and falling clients, identifying the revenue at risk and acting before you actually lose revenue, or worse, a client? AI can do all of this faster and better than even the best managers. With these tools available today, why aren’t businesses taking advantage of them?
Singletrack can help you ambiently collect all the information your contact with clients generates, and apply analytics supported by AI/machine learning to interpret it and build it into your key management decisions. By making best use of all the information at your fingertips, and embracing new ways of communicating with clients, sell-side research providers can continue to be successful - even in a difficult climate.
How do we know? We see good results with our clients. Bespoke email contact generates up to 8 times more opens than standard bulk mailing. And over the past 3 years, our clients have increased research production by 30% per year and seen an increase of more than 20% in engaged accounts. I don’t think anyone would argue with that level of success.
The best part is, sell side research providers already have many of the tools and much of the information they need to thrive. It’s just a question of using it.
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