— Read on for the equations —

As marketing leaders, we must put a value on the financial impact of inaccurate data!  So, here’s a quick and easy method to do so, with an equation below to identify your missed revenue.  

We all know that Data is the core of every campaign – just ask SiriusDecisions. So, we know every campaign needs to be built on good data. Without the right target audience and target persona, even the best messages will fall on deaf ears. Fact!

Correcting poor quality or old data, directly increases revenue potential. Below I will show you how we measure the impacts on campaign performance.

First, let me put this into perspective – E.g. if a caller makes 80 calls and the data was 20% inaccurate, the caller was only productive for 80% of the day (making only realistically 64 prospective calls). Therefore, how do we attribute a cost to the wastage of 16 calls?  

Well, for every 5% gained in data accuracy we increase revenue potential

•      B2B Example – Objective is $1.2m pipeline, average deal size of $50k. If 5% of the data we called is inaccurate, we can expect that we lost out on a potential of $60k pipeline. If the data is 15% inaccurate – this is whopping $180k worth of potential revenue missed! (example based on 1% cold call to lead conversion rate, and 10% lead to closed won opportunity – observing a conservative conversion rate)

Want to know how we get this figure? Read on…

The majority of our data frequently has accuracy issues. Although some lists can also be extremely valuable with the right intelligence, and therefore they need to be maintained. On average, Connect Marketing improves the quality of client supplied data by at least 5% through August cleansing activities. (August being the marketing low period for any new marketeers).

Some example assumptions for this equation

Working on a: 1% of cold data being converted to leads, 10% leads convert to revenue

$1.2m is the objective revenue and $50k is our average deal size

Records needed: first we must know how many records we have or are required.

Pipeline Required Value ÷ Average Deal Size = Required converted opportunities

$1.2m ÷ $50k = 24 opportunities required

Required converted opportunities ÷ lead to closed won conversion % x 100 = required leads

24 ÷ 10% x 100 = 240 leads required

Required leads ÷ call/email to lead conversion % x 100 = required number of records

240 ÷ 1% x 100 = 24000 records required for revenue target

Revenue MISSED @ 15% Inaccuracy

Number of records ÷ percent of inaccuracy = number of inaccurate records

24000 x 15% = 3600 inaccurate / wastage

Inaccurate records x call/email to lead conversion % = missed leads

3600 x 1% = 36 potentially missed leads

Missed leads x lead to closed won conversion % = missed closed won opportunities

36 x 10% = 3.6 potentially missed closed won opportunities

Missed opportunities x average deal size = missed revenue

3.6 x $50k = $180k in missed revenue

Conclusions:

Businesses need to regularly cleanse their marketing data. The summer period for marketing is usually the best time to revitalize data to meet the demand of marketing plans designed for the last quarter of the year. 

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