We humans often make decisions within seconds, based on emotion and intuition. We are largely emotional in nature. But when it comes to important business decisions, it is critical that these are based on as many factors as possible, and that they are based on facts.
Using data and not gut feelings when making business decisions is something that all companies have challenges with, which is also an incredible opportunity to grow your business.
On Thursday, March 31st, we gathered at Leadfront together with some selected B2B sales and marketing managers and discussed challenges and success factors for making data-driven decisions. We discussed data quality, ownership in the organization, the importance of having common processes, as well as models to understand the importance of different activities throughout the buyer's journey.
We have summarized some of the most interesting discussion points from the event below, categorized into perceived challenges and common success factors.
A good understanding of the current situation lays the foundation for improvement.
Reports and dashboards based on data are only as good as the underlying data. If work processes are not followed, it can easily lead to wrong decisions.
Data silos and one-way integrations are a common source of problems when it comes to data quality. Not being able to clean data at the source leads to data at the destination being continuously overwritten with incorrect data, which simply leads to not being able to trust the data.
In the sales organization, it is common that data is collected by the sales people. Not entering the data continuously, in the right format and according to routines and processes is one of the biggest challenges for sales. This leads to a picture of the data that does not match reality, resulting in incorrect decisions being made.
Salespeople's revenue models and focus on quick and short-term sales goals set the stage for salespeople to prioritize, which can easily lead to the deprioritization of data collection in a CRM system. To change this, you need to change the source of the problem and give salespeople clear tasks and ensure there is time, support and understanding of why it is important to follow these processes.
The common division between marketing and sales can easily create challenges, not least in creating a common understanding of the customer journey and how to measure and value the different activities that make up the customer journey. Discussions can easily arise around which function or department contributed most to a deal, when in reality there have been a number of interactions of different parts of the company that contributed to a deal.
Driving change is not always easy, as people have a natural resistance to it. As a leader of the sales and marketing department, it is important to find support processes and tools to help the team move towards a desired state. Of course, it is important to remember that change management requires hard work and patience, and should be seen as a process rather than an activity.
Having common definitions in the SMarketing process (from site visitor to customer) is the foundation to start measuring, analyzing, and drawing conclusions from your data.
The common process changes over time. It is important to continuously work on the process as the business and customers change.
To interpret data correctly, you need to take into account different aspects and perspectives and try to build a picture of the whole and not get caught up in focusing too often on individual data points. For example, a good graph for analyzing delivery between different service desk agents takes into account the different aspects of a service desk agent's delivery such as the number of cases closed, the type of case and customer satisfaction.
In order to maintain data quality in the organization, it is important that all department managers are trained in the data issue, and take responsibility for the data collected and processed in the respective department.
Management must be aware of the importance of data quality and its impact on higher-level decision-making. A management that takes an active role in these issues creates a better condition for department heads to prioritize correctly further down the operational level. It is increasingly common to design a function with overall responsibility for data and data quality.
You need to prioritize data and assign responsibility for data quality to different people. For example, a web analyst has the main responsibility for data quality in data collected and analyzed for web visitors.
The most common source of inaccurate data is the human factor, through, for example, carelessness, ignorance or disinterest. Therefore, it is worth reducing the need for manual data entry, both in terms of data you collect from customers and web visitors, as well as from sales or customer service. Connections to third-party data to populate and update data are a good way to streamline and at the same time improve data quality.
A joint team (e.g. Revenue team or Growth team) with members from both sales and marketing can be a good replacement for the traditional approach. This will be a good basis to see the customer journey as a whole and analyze which activities drive the customer through the buying journey
As a department manager, you drive the behavior of your team members. It is important to keep this in mind when measuring and rewarding employees based on a specific metric. You do more of what you are measured on.
Important with a common view between marketing and sales - Defining leads together creates better quality in both directions.