Is your business making the most of the full range of data platforms available? Becoming a truly data-driven company gives you access to actionable insights that you can use to shape your business approach.
You’ll end up with a more efficient company if you use data to tell a story and piece together your customers' intentions, desires, and habits. Say goodbye to marketing dollars spent on a wing and a prayer.
Data-driven marketing and sales can increase revenue and reduce expenditures at the same time. In this post, we'll take a look at how big data platforms can increase your audience engagement, revenue, and improve your brand as a whole.
Ready to find out the best business metrics for data-driven companies and how you should be using them? Stick around and find out more!
Step 1 - Set your data-driven goals
Data is not a final product. You can have all the data in the world on customer buying habits, likes and dislikes, how many customers you gain and lose per quarter: none of it means anything unless you use it wisely.
In order to integrate data into your marketing and sales strategies, you will need to set goals for your data and parameters for how it will influence your decisions.
For instance, is your goal to reduce your churn rate? Then track your churn over a long period and determine the common behaviors of customers who leave.
If you want to increase revenue, use sales data to see what sells and what does not not, and re-orientate your catalog or sales strategy accordingly.
Data is a tool, a means to an end, not the end itself. It’s best use is in helping you make better, smarter decisions.
Step 2 - Give the right access to data
Who uses data at your company right now? Do you have a dedicated analytics team that analyzes it with a fine-toothed comb? Does the marketing team use data to plan their approach? Ideally, anyone in the company who interacts with customers has access to data relevant to their function.
For instance, marketing needs to have access to the churn rate, the email click-through-rate, the average customer acquisition cost, among others. Sales need to have access to the sales data across products and services. Customer success needs to know average wait times and time to resolution on support tickets.
Every area of your company can benefit from using data. A big mistake is giving one section of your company access to data while leaving the rest of the team with spartan scraps or nothing at all.
Step 3 - Pick your metrics
What do you measure? What data do you need to evaluate initiatives? Each department has its own needs, so let’s take a look at examples of metrics by department.
Data-driven marketing is a fantastic use of data. You should track:
- Qualified leads: contacts who are more likely to become customers
- Social engagement: comments, likes, and shares on content
- Customer acquisition cost: the difference between revenue earned per customer and the cost to bring them on
- Web metrics: monitoring quality data like bounce rate and average time on site
- Conversion rate: the percentage of prospects who convert to customers
Data-driven sales are closely tied to data-driven marketing, but the metrics are different. Your sales department should be tracking:
- Quota fulfillment: The number of people on the team who is consistently meeting their quota
- Average deal size in dollars: you can break this down by time-frame and salesperson
- The sales funnel: both successes and problems
Customer success metrics
The importance of excellent customer success cannot be underestimated. The best way to improve customer success is to use data-driven decision making to refine your processes. To do this, you should track these metrics:
- Number of issues logged and resolved daily
- Time spent on each issue
- Call wait time
- Escalation requests
- Customer satisfaction scores
Management is not exempt from data. If anything, data-driven decision making is even more critical at a management level. Track these metrics to improve your company's management decisions:
- Employee satisfaction: are your employees happy with their leadership?
- Productivity and average revenue per employee
- Downtime and its cost
- Actual cost and value of projects
- Return on investment for projects
Step 4 - Define who collects and collates data
Who is going to oversee collecting all the various kinds of data we discussed? In most cases, the responsibility for collecting data will fall on the heads of each department. Once they pass this data on to management, you will need to collate the data into something usable.
Having a central system for all the data is a good start. Analysts within your organization can look at the data stack as a whole and feed relevant analysis and trends back to heads of department. Your teams can then put the insights from the analysis into action.
Step 5 - Use the right tools to analyze data
Analyzing data may sound like an esoteric talent and something that will yield naught but incomprehensible graphs and meaningless collections of numbers. If you use the right tools, the outcomes will be much more useful.
There is a massive collection of tools out there that can help you get the most out of your data. Examples include Power BI and Tableau, as well as tools that are designed for specific company departments.
Using the right tools can turn your data into beautiful and readable charts that make data accessible to anyone who needs it. If you do not have the right tool set, chances are the data will not be useful.
Step 6 - Train your staff
To get the most out of the data available, you need to train your staff in data literacy.
Data literacy is quickly becoming an important field, and many quality accredited training courses exist for employees. If you have the budget for it, every customer-facing employee should get training so they are prepared to use data to its fullest extent.
Step 7 - Hire data experts
We recommend hiring data experts if you have budget available. Hiring qualified consultants to help you overhaul your approach to data collection can improve all aspects of your business and give you a sustainable model for the future.
For instance, data analysts can help identify the most useful metrics for your company to track. They can develop models for data-driven decision making and ensure that your choices have logic and rationality behind them. This is particularly important if you are a newcomer to a data-driven strategy.
Step 8 - Update your data stack regularly
You collected your data, what’s next? If your first thought is anything besides refine and refresh that data stack, you are not taking the best approach. Data is only useful if fresh.
Customer habits, spending, and responsiveness to various marketing techniques can change over a short time. If you are not adding new data to your stack, you are not getting the most out of your data, and your decision making will be hampered.
You should always be collecting some facet of new, relevant data. Help motivate your heads of departments to make it a priority.
Step 9 - Reward employees for using data
A data-driven strategy is still quite a new aspect of customer success for many companies, particularly small businesses. Modern technology makes it easier than ever to collect and analyze data. Yet, data-based decisions might be a new way to thinking for your employees.
Holding your employees accountable for their use of data can help positively change the culture. For instance, you can reward employees who make data-driven decisions in a meaningful way.