If you're a small private equity firm or boutique investment bank, the phrase 'big data' might not mean anything to you. At a high level, big data refers to the challenges of managing enormous amounts of customer, employee and other data that companies possess. Healthcare companies might leverage big-data tools to predict the likelihood of disease, while a bank would want to analyze which age brackets and zip codes are most likely to download a mobile banking application.

For a middle-market private equity firm or investment bank, spending time and money on harnessing big data might feel like a 'nice to have' vs. a necessity. After all, the databases within this market typically aren't that sizable-both in terms of volume and depth of information. If your sweet spot is consumer goods companies with Ebitda of $10 million to $30 million, the universe of potential targets and their executives is only so large. Perhaps you're generating enough deal flow with a few analysts, some outbound email marketing and sending your key people to the right conferences.

But that doesn't mean it will last, so don't get too comfortable.

The dealmaking business is only going to become more competitive as time goes by, not less. And one of the reasons for that is because technology has made the competitive playing field more level-and more open to newcomers. Whether you're a new PE firm or a one-man boutique investment bank, the barriers to entry are lower than they've ever been. Nowadays, building a website takes weeks, not months, and a few bucks on Google AdWords will bring you some starter web traffic.

Today's Internet also provides several ways to research and seek out customers. The growth of social media networks, such as LinkedIn, means both companies and individuals are providing more information about themselves that can be searched easily. At SourceMedia, for example, my telesales team utilizes LinkedIn for Salesforce, which populates Salesforce with LinkedIn profiles that match the names and companies of the leads.

In addition, there are a host of online tactics and web analytics tools that allow for customer profiling. Some of these tools link IP addresses to specific firms and people, while others focus on user paths.

When you leverage such tools and tactics, your marketing activity becomes less art, and more science. The smaller your staff, the smaller your marketing team, the more important it is to get granular with your marketing. Not only is it more scientific, but it has the potential to save time by automating your marketing efforts.

Your sales organization should be an equal partner in this. Having a customer relationship management system is a must, but unless you give that staff access to metrics, analytics tools and data, your endeavors around big data will only be half as effective.

Here are a couple of examples of how big data can increase your efficiency and return on investment:

* Deal prospecting. Let's say you're an investment bank entering a new sector, and you want to introduce yourself to PE firms focused on that sector. Instead of casting the net widely in a mass e-mail to all the PE firms in your database, you can match that list against other data sets to determine which relevant firms possess contacts within your team's LinkedIn networks.

* Marketing to customers based on their content preferences. We've developed several custom e-newsletters for clients, most of whom use them to create a relationship with potential customers. If you have the right reporting tools, the client can examine which content resonates with which users and how quickly they open the e-newsletter. Then you can tailor your message, as well as the timing of that message, to maximize its effectiveness.

Financial services industry Marketing