The innovations we’ve seen in cloud computing, mobility and artificial intelligence have been amazing, but so far there’s no technology that can allow busy entrepreneurs to create replicas of themselves.
If you’ve launched a small or medium-sized business and have watched it grow, you know how great this kind of capability would be.
As one of you continues to make more sales, the other one would handle things like marketing, or customer service.
As one of you attends industry conferences and events that teach you new ways to scale, the other could be applying those takeaways and reaching new milestones in your business plan.
While one of you sleeps, the other could deal with all the things that haven’t gotten done.
Instead of hoping for a clone, though, most entrepreneurs turn to a more traditional method: hiring people. This, of course, brings some other challenges.
How will you attract the right people? How much will you pay them? Are you collecting the kind of data they’ll need to be successful?
That last question may be the most commonly overlooked, but also the one that makes developing the right team exceedingly difficult.
As the owner or founder of a startup business, you might feel like you’re already swimming in data. You know, at least roughly, who your biggest customers are and the opportunities to increase the amount they spend with you. The most common service issues? You know them by heart. You also know which marketing channels are converting into leads.
Once you start looking for talent, winning them over and onboarding them, you not only have to teach them how to do their jobs, but also how to access the data that may have mostly been in your head until now.
Besides goals or objectives for each new hire, you'll also need to establish and explain the metrics that will be used to evaluate their performance. This is how it’s done:
How to identify the data that drives decisions
The one downside of data collection is that there are almost limitless choices in what you can examine and apply to your business.
It will become overwhelming (and frankly, not very useful to you or your growing team) if you don’t prioritize certain kinds of data over others.
You also don’t want to do all the data collection and analysis manually. That’s what tools like CRM were designed to assist with in the first place.
Think about what really moves the needle in terms of capturing customers’ and prospects’ attention, and what leads to closed deals. Here are a few ideas to help you start brainstorming:
- What are the key details that help suggest where customers are on the buyer journey — are they in the awareness phase, are they researching products and services, are they considering multiple vendors or are they ready to make a purchase?
- What are the most common objections to making a purchase? What additional information is most likely to overcome those objections?
- What tends to influence the pace at which the purchase cycle happens, depending on the size, industry or other attribute of a customer or prospect?
- Where do customers and prospects “drop off” or decide to wait for a prolonged period on a purchase? What levels of additional authorization or approval might they need to seek?
- What kind of marketing content best serves customers at each stage of the journey? Do white papers help lead to a buying decision, or do they prefer to see case studies, for example?
- What kind of average time to resolution on service issues is necessary to prevent customer churn after they’ve purchased a product?
How to choose and manage your metrics
There’s an old adage in business that goes, “What’s measured gets managed.”
If you and your team aren’t able to quantify the things that show you’re progressing as a business, in other words, your progress will be limited.
The tricky part is picking the right metrics, because, as with data, there are so many to consider, and not all of them will be worth the time and effort.
Lots of companies might look at the number of sales leads they collect through marketing, for instance, but what if the majority of those leads don’t represent people with an intent to buy?
That’s why many companies have their reps look over leads and measure the volume of what are called “sales qualified leads” or SQLs.
Similarly, it’s tempting to measure the effectiveness of sales teams by how many cold calls they make in a day or even how many meetings they book.
What really matters from a bottom line perspective, however, is their win rate or close rate. When you see that go up or down, you’ll know whether you have to take some kind of action or not.
Managing metrics, meanwhile, will become easier if you think about cadence and frequency — how often will you have to look at a particular metric, and do you need to get data on other metrics first?
You should also think about the span between input to insight to action. When you choose a metric, in other words, can you take raw data and analyze it fairly readily? Or will you need to pull together several data sources from different areas or systems and use additional tools to make sure the metric is accurate and you can use it?
Data and metrics as a discipline
Effectively using data and metrics in your business will take some time and practice, just like any other skill. It may have to happen in parallel with hiring the first employees who help you reach the next stage of growth.
This means you may occasionally discover you’re measuring the wrong things, or that the data on which you’re basing a particular metric is incomplete or somehow flawed. That’s okay, as long as you recognize those issues as they come up and you work as a team to refine your approach.
Companies that make data and metrics a core part of their business processes are able to become more organized, more efficient and more likely to delight their customers. It’s better than having an entire army of clones.
