How Much Should You Charge Your Clients? Data Analytics Has The Answer!
Data analytics can help attorneys win new clients and make these clients profitable ones.
Data analytics can be a great tool for the forward-thinking law firm looking to increase profits. There are two problems standing in the way, though. The biggest single problem that businesses face in effectively using data is that they don’t have they data they need. The second biggest problem, in my experience as a consultant, is that firms do not understand what data analytics can do or how to use data.
In fact, data analytics has the power to answer many important questions for businesses, including one that is at the heart of the law business – how much should I charge a client?
Pricing analytics is a huge untapped opportunity that firms across the economy are only just starting to take advantage of. (Try this book to learn more about pricing segmentation.) Pricing differentiation is taking hold in travel, for instance – look at a price for a plane ticket on your smartphone versus a computer and you will probably get two different prices. Look for a plane ticket price on a weekday versus a weekend, and you will also get two different prices. These prices are driven by data analytics. Law firms can take advantage of the same concept.
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The basic idea here is simple – if you charge all clients $20 an hour, you will have clients calling all day, but you won’t make any money. If you charge $5,000 an hour, you would be enormously profitable if you could keep your existing clients, but they will all leave.
The key then is charging clients their maximum willingness to pay. Some clients are willing to pay a lot because the attorney adds tremendous value to the client’s business, and other clients are much more willing to shop around.
Pricing analytics can also be extremely helpful in winning new deals and clients. (Just be sure you understand what you are doing with data analytics before jumping in with both feet though!) Law firms dealing with big corporate clients know that they are often not the only firm being considered for the work. And of course, price is not the only factor by which clients make a decision. But it is a factor. Data analytics can help attorneys put together a client proposal that maximizes the chance of getting a new client, and making that client a profitable one.
Calculating ROI for data analytics can be tricky, but several studies on pricing differentiation in the broader business world have found that returns on investment for data analytics average 56% annually. Maximizing that ROI is key, but the returns figures should be welcome news to any firms looking to use their resources effectively.
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The quest for maximizing profits by charging differentiated prices starts with what is called a two-stage regression. Attorneys need to make sure that the price they charge will win the confidence of a new client, and will not drive an existing client away. This requires using a logit regression.
A logit regression examines multiple different variables related to the client and the law firm – base hourly fee of course, as well as other factors like number of attorneys, length of time the client has been with the firm, geographic region, etc., and then determines the probability of those clients leaving (or not engaging the law firm in the case of prospective clients) based on a mathematical formula.
Where does the data for this logit regression come from? It has to be gathered. That process is not easy, and it requires an investment of firm resources, but it can make a big difference in firm profitability and client retention. (A similar analysis can also be done to help the firm proactively identify the clients at greatest risk of leaving the firm, so that special efforts can be made to keep them onboard.)
With the logit regression complete, it’s time to consider the second stage of the two-stage regression analysis. The second stage of analysis requires taking the output from the mathematical equation in the first step, and then using it to modify the base hourly fee for each client so that it maximizes overall firm profitability.
Some of this may seem complex, and undoubtedly many attorneys would prefer to just continue using their tried and true business model. Doing that is leaving money on the table, though. Data analytics has a learning curve certainly and requires an upfront investment of money and time by firm partners. But once that investment is made, the results can pay major dividends for the firm over time.
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Michael McDonald is an assistant professor of finance at Fairfield University in Connecticut. He holds a PhD in finance. Michael consults extensively with organizations ranging from Fortune 500 companies to start-up businesses on financial matters through Morning Investments Consulting. Michael has served as an expert witness in legal disputes, and is an arbitrator with the Financial Industry National Regulatory Authority (FINRA). Michael can be reached at [email protected].
