Struggling to manage your sales data is the kind of 'problem' most start-ups would die for - at least it means you have customers. But even in the earliest part of the sales cycle, capturing and analysing customer data could prove critical further down the line.
If your sales team's idea of information management is to log their prospects' contact details in a spreadsheet and file client business cards in alphabetical order, it might be time to introduce them to some of the newer techniques that have become possible over the last few years. Even if your biggest problem today is getting early proof of concept sales, keeping a grip on all the relevant information quickly gets problematic once your business moves out of the development stage, particularly if you're in the consumer market or have a dispersed prospect base. It's not just about better administration - for some companies it's about cutting the cost of doing business and increasing the chances of clinching deals.
Even in the software-savvy hi-tech sector, sales automation software has enjoyed something of a mixed reputation in the past, particularly among more experienced sales professionals who rose up the ranks using little more than a Rolodex system and pen and paper. Some people still tend to think of it as a computerised contacts list and wonder what the fuss is all about - this, after all, is why personal organisers were invented. In smaller start-ups, where even the most mundane sales-related information tends to be shared with everyone on the team, the idea of purchasing a system to record sales data seems like overkill.
At their most basic level, however, sales automation systems provide security for a key asset - customer information. How much of your sales information will walk out the door if your sales director misses target once too often and decides to try their luck elsewhere? Do you know what your customers and prospects are telling your team about their future purchasing plans and product needs, and do you have a grip on all of the sales objections they're coming up with? How easily can you get a snapshot of ongoing sales activity and assess the strength of the prospect list if one of your investors calls for an update? And can you measure how effectively your sales team is working - how many calls are getting through; how many face-to-face meetings they're setting up; or how long they're taking to close each deal and what its value is?
This kind of information is routinely captured in sales automation systems, which bring a combination of process control and business intelligence to the whole sales set-up. At an operational level, sales systems bring a degree of administrative efficiency as the volume of prospects increases, providing templates for commonly-used documents and alerts for follow-up calls. They also give salespeople easy access to details of past conversations with prospects and customers detailing their business pain points, IT budgets, previous objections, competitive data and so forth. Managers of larger sales teams can also use the functionality to control leads centrally, which speeds up processing time in high-volume environments and allows organisations to allocate leads more effectively. Some sales systems also provide insight into marketing effectiveness: after running different campaigns, leads can be allocated to their source to see which approaches delivered the best return.
But it's in the field of business intelligence that sales automation promises the most significant long-term benefits, particularly for small business managers who tend to spend more time finding and collecting information about their business than actually analysing and acting upon it. The greater the analytical capability that's built into a system, the more powerful it will be. Because sales effectiveness is so critical to a business as it moves out of the development phase, there's often an assumption that management will already know the most important details, but it isn't always easy to take a step back for trend analysis. Analysing sales activity quarter on quarter, for example, gives you an additional perspective on current performance. Likewise, forecasting becomes more reliable if you have a rich historical context; if past records show that lead times in certain business sectors are long, that may influence your estimates as to when sales will close.
Many of the largest sales automation software vendors now provide this kind of capability for smaller businesses. They include Sage, which sells several applications including ACT! for small business and Saleslogix for mid-sized companies; Salesforce.com, which hosts sales software remotely for users to access over the Internet; and Siebel Systems (currently being acquired by Oracle), which was the leader in customer management software at the enterprise level and has more recently targeted the SMB space. As a measure of pricing, Salesforce.com offers packages starting at �45 per month per user, or �690 for five users.
There are of course some caveats. Firstly, like all user-based pricing, the monthly bill or package licence fee will go up as the volume of users climbs, something that's particularly worth bearing in mind in sales automation where access may be required from multiple departments. Secondly, it's important to establish how flexible the system is in terms of searching and slicing and dicing information: it's all but impossible when you first implement a system to know what kinds of reports you'll want one year down the line. Ease of integration will also be a factor in the future: for example, some organisations link sales to credit control to ensure sales staff are up-to-speed on accounts that are on credit stop.
Most importantly, as with any analytical exercise the quality of the analysis will depend in large part on the quality of the raw data - and that data is generated through day-to-day use of the system. If you really want to have strong historical insight into your sales effectiveness, the earlier you start collecting data the better.
By Keith Rodgers