An article by Simone Göltl and Sebastian Hartmann, October 2019

A lot has changed in both consumer business and the B2B space over the past decade: More and more technology has transcended our everyday lives, data and knowledge are easily accessible and we can buy almost anything with a mouse click or a tap on our screens. The so-called “digital natives” are taking over significant responsibilities in many companies – and they are changing the way many companies think about both client and supplier relationships, the sourcing of professional services and how services and solutions should be delivered. 

So, what does all of this mean for the “client whisperers” and “rainmakers” in law firms, consulting, accounting, tax advisory, design or marketing agencies? What does it mean for anyone, who is in professional services and needs to cater to a client’s needs and challenges? What does it take to “upgrade” the traditional relationship-based sales approach for the future?

Before we answer those questions, let’s dissect a few stereotypes (or misconceptions?) about sales in B2B and the possibilities of data and analytics in a traditionally relationship-based world of professional services:

B2B – It is a people business, or is it not?

Before getting to deep into B2B, let’s think about our very own daily consumer preferences: As a customer I want to have transparency about a product, its value proposition and, of course, the exact price. I want my needs to be met – preferably as soon as they arise. So why wait until the bookshop opens? Digital e-readers can provide books with a single click. And I want a salesperson or interface to be informed about or even anticipating my needs right away. By the way, most people whom I know, also expect that exact same transparency from their tax advisor – that is only for those, who have not yet replaced their advisor with a piece of software yet. Yes, I am one of those “digital natives” – and our generation changes B2B sales and purchasing from within. Right now. Including consulting, tax, marketing, and law firms or any other professional service.

The long tail of clients: Nitty-gritty work or huge potential?

Blessing and curse at the same time: Large professional service firms (PSFs) are often fortunate enough to be blessed with a long tail of clients. But time and money constraints do not allow them to service all clients equally. There is no dedicated account manager or team available for every single client of a large PSF – and the traditional account managers and teams cannot stay on top of every client’s development and situation, the industry trends and peer group’s competitive moves.  Therefore, most PSFs tend to segment their clients in different account groups. And only a few dozen clients or so are managed at the ideal “service level”. But what about all the others? How much potential is evaporating unnoticed in the long tail? How much disappointment about the lack of insights, foresight, and anticipation from the “trusted advisor” can a relationship with a “low priority” client bear? B2B analytics can effectively steer your limited resources towards emerging client demands or challenges, to the next best offer and best fit solution. 

We do whatever the client needs! But what exactly is that?

Data about a professional service firm’s offerings, services or solutions is usually available – sort of: PSFs typically advertise their capabilities under classic or trendy high-level headlines. My favorite one: “Digital Transformation” – it doesn’t get any fuzzier, does it? The fluff continues in terms of their own financial data: Most firms may know how much revenue each partner is bringing in, how many hours their workforce is billing or what level of utilization is achieved for certain groups (typically based on roughly defined capabilities, often grouped into profit centers). Revenue numbers can also be analyzed per client. But if you were to ask about the exact portfolio of services or solutions delivered, the answers start to get very fuzzy or end at a high-level view. A clear understanding of contribution margins per exact offering across multiple clients is typically very hard to come by – and the operational figures along a PSFs value chain are often not even considered to be relevant. Which may be OK in a very traditional setting, comfortable market and very high margins – but that space is getting smaller and smaller. Last, but not least: Clients want specific, robust solutions – and reliable delivery. Even “bespoke” solutions are to be architected based on trusted components, modules, services, and products – and that means “data” today. So, when it comes to selling something, you better show up with a very tangible answer: 

“In God we trust – all others must bring data”.

We know that all these challenges above can be overcome – and we have worked on this journey for the past couple of years in a number of settings for different firms. Embarking on this data-driven journey clearly leads to unlocking unprecedented sales potential and value for clients both within the existing and potential new client base. So here are three key recommendations to start your firm’s journey towards next-generation “sales intelligence”:

Recommendation #1: Build-up the treasure – tune into your “data potential”

A great place is to start is your “master data” – especially about your firm’s clients and the exact solutions, projects, services, products, etc., ideally in connection with your financial views. Take a look at where you generate data today (e.g. client acceptances and onboarding, time bookings, billing, etc.) and make sure that your master data fields serve your strategic and operational management needs alike. Systematically enriching these traditional sources by integrating and linking them with alternative data sources and external data (e.g. financials, news, announcement) will open the next level. And as your firm’s “solutions” are becoming more and more digital at their core, their delivery and usage also generate incredibly valuable data about your operations and your clients’ usage of your solutions. Of course, this thinking is nothing short of a fundamental paradigm shift for many traditional PSFs. Those firms capable of embracing it, are likely to dominate – sooner rather than later. But it is okay to start with cleaning up your master data and basic data sources first (NOT an expensive CRM tool!). Really! First, we crawl – then we run.

Recommendation #2: Focus on key actionable sales analytics – and ignore the “art of the possible”

Many data scientists love to explore the borderlands and frontiers of what is possible. However, even simple descriptive statistics can “fuel” your sales teams – and are easier to transport and explain than an “almighty intelligence tool”. Peer group comparisons across your client base, heat maps of correlated solutions (services/products) or trend analytics can quickly reveal actionable insights. It is those kinds of basic recommendations that allow a salesforce to effectively use the limited hours in the day to focus on the “likely” demand potential and thus the “next best offer” or “next best client”.

Of course, you need to iterate and keep developing those analytics – by talking to clients and sales teams alike. That’s also a prerequisite to employ Machine Learning in a reasonable way. Smart microservice architectures, for example, in modern analytics platforms can get you going quickly and at moderate investment levels. Their flexibility for experimentation is crucial in this space: Sales analytics are much more about iterating and exploring than about perfection.

Recommendation #3: Package your sales analytics – and start with a human interface for your professionals 

A dedicated sales analytics team can build a “bridge of understanding” to your salesforce, leaders, partners, and managers, who are in touch with clients. They basically only want to know “which three actions can increase sales figures today” – across their specific focus clients, their solutions and teams. Make it easy for them – and tailor and package your analytics output to your users. Usually, they really don’t need to understand the subtle complexities of algorithms, data sets and the complexity that comes with it. They need answers: ‘To whom shall I sell what (and why)? And what else do I need to know about my client’s potential demands and his peers?’ When they are more convinced, you can start to slowly switch towards self-service interfaces and automated insights delivery.

Following these three recommendations will establish the foundations for scalable sales intelligence in a professional service firm:

So, stop chasing clients – start chasing data. Your clients will thank you for it.

This article was originally published on LinkedIn.

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