This is part four of a four part blog series.
In my previous blog posts in this series, we looked at understanding the core value of our digital property, followed by modeling the benefits of personalization. Now let’s look at investment costs associated with implementing personalization and calculating our overall ROI and value.
First, estimating investment costs: We need to look at implementation project costs and ongoing operational costs associated with personalization. I typically use a 3 year timeframe to calculate Total Cost of Ownership (TCO). The cost categories for implementing personalization are roughly the same as those for building and maintaining a traditional website. The chart below illustrates splitting build and maintain against creative and tech.
Just with building a website, there are no hard and fast personalization figures for each cost category above. Some organizations may allocate costs 1 & 2 as one-off project costs (Capex), whereas others may smooth these costs, absorbing them into 'business as usual operational expenditure (Opex). But broadly speaking, these categories stand as a useful way to separate and estimate costs. I go into more detail on this below, in the example.
Once we’ve modeled the investment costs, we can simply move to Step 4 which involves subtracting the costs from the benefits, to arrive at an ROI. Again, this is typically measured over a 3 year timeframe, in order to calculate the total net benefits, or the project’s net economic return. Finally, we can detailed the non-financial impact to provide an overall value case, as outlined in my first blog in this series.
So, now time for an example.
Step 1: Let’s take a mid-size retailer with an annual revenue $300m / yr. Roughly 12% of revenue, or $36m, comes directly from the commerce website.
Let’s assume this is the baseline value pre-personalization; $36m per year, or $3m per month.
- We can see the site has 2m visitors per month and 60,000 transactions per month. A conversion rate = 3%
- The average online revenue per user (ARPU) is $50, with 60,000 transactions per month, giving $3m revenue.
- Sales are seasonal so the exact number varies by month. What is interesting here is not necessarily the exact numbers but more the relative numbers before and after personalization. So, we need to ensure we’re controlling for any seasonal, or other, differences when it comes to testing our hypotheses, that personalization will increase conversion rates and revenue.
- The site also advertises third party products and makes $4m / yr in revenue generation from ad revenue and referrals.
- In addition, the site has a lead gen / awareness / brand building element and also has some product support information, although we’re not quantifying that value here.
Now, let’s assume the retailer has grown 5% each year, so we’ll fairly model a 5% growth each year regardless of whether we implement personalization. Ad revenue remains flat. We could model something like this: