Over the past twelve months, we have seen seismic changes in the political and business landscape. The votes for Brexit in the UK and for Donald Trump in the US have been used as proof that we are entering a “post-truth” economy, where expertise is devalued compared to feelings and intuition.
At the same time, the marketing discipline has been looking to increase its use of data for decision-making and budgeting. Getting more information from digital channels on the success of campaigns has driven a change in how marketers work with data and try to link their decisions to revenue.
However, this may not go as successfully as many marketers might hope. Let’s consider an example – a marketer wants to make a change in pricing strategy based on data. Using a combination of industry trend data, current sales and marketing forecasts, performance reports and financials, the marketer in our example might present a new approach around a product. This could present a real market opportunity to grow share in a product category and be backed up by analytics on current performance.
Then the CEO says “No.”
Now, this decision might be based on external information not captured in data – for example, previous approaches around pricing in a particular way that did not historically prove to be successful. Alternatively, it might be based on an emotional tie to where the company exists in the market currently.
How can marketers avoid getting into situations where these decisions are either rejected or their data not used? In a political and business environment where the emotional impact is just as important as the facts, how can marketers convince their management about the best approach to take?
Ironically, it seems the best approach will rely on using data in smarter ways. Rather than looking for more data, putting information into context can help build more emotional attachment.
To get that more contextual picture will require data from outside Marketing. For example, sales teams should be able to provide data on how marketing leads were processed and converted into customers, while finance can provide detail on new bookings and invoices getting paid.
However, using this data is not as simple as just combining individual reports. Instead, the goals that each team should be working towards may need to be amended as well. In this example, targeting Marketing teams on the volume of leads alone can affect Sales conversion rates. Looking at higher quality leads rather than volume can be more effective overall.
Networking business and data together
The issue here is that many companies have rarely standardised their key metrics. What counts as a lead to marketing might not pass muster for sales, while revenue counts for sales may not reflect invoicing and payment plans for finance. Alongside this, the spectre of governance is always present too, where people may not be working from the same sets of data and definitions.
Bridging this problem relies on establishing common and reusable definitions and sets of data that can be networked together. By networking data across the business, everyone should be able to pull from the same consistent sources of information.
After this, it’s a case of building a wider picture of decisions in context. Showing how marketing and product decisions might affect sales and revenues can help demonstrate that choices made can have a more material – and more emotional – impact. However, looking at this context can help marketers create a better story around their data in the first place.
The other benefit is that marketers will have to work more closely on how to use data for analysis with others. Putting together key value indicators that multiple departments drive can help build more emotional investment in the end result. When each team feels like they are integral to how the whole company meets a goal, the emotional pull will be greater.
This approach to goal-setting and making use of data can help everyone see how their decisions have an impact on the business. More importantly, this joined-up approach can support putting together a more convincing emotional argument for decisions that have to be made. By putting data into a wider business context, it’s possible to bring emotional response and analytical decision-making together.
This article was originally published in Digital Marketing Magazine on April 11, 2017.