Modern Insider – Online Marketing Blog

Every day you’re measuring your ecommerce sales, optimizing campaigns and getting just the right offers in place to beat this economic gloom. Things seem good, the boss is and all is going well until the end of the quarter hits and John finance comes running into your office screaming about how you’ve sunk the company with horrible bottom line sales? Ok, that may be a bit of a stretch but the issue is no laughing matter – analytics are something almost every ecommerce site has learned to take seriously and for good reason yet many marketers still look at the top level only leaving a great many unknowns until the books are closed hours, days or even weeks later.

The internet provides for data driven marketing in a way just about no other medium can. But making the right decisions requires more than just data, it requires having enough pieces to find the right ones in the middle of the mess. In the case of sales that means understanding both top and bottom line revenue due to promotional discounts, shipping subsidies and so forth. When all this data comes together the results are single data points that tell a story about conversion value but when left alone what shows is summaries that don’t really explain if a campaign made waves or made dollars.

While average order values are a commonly used tool for getting around measuring cost of goods they’re no substitute. Assume for example that your average order for the last year was $100 with a profit 40% margin leaving you $40 to cover marketing and other variable costs. On the surface a mid-year for a new product campaign with a $10 cost per acquisition and a $9 free shipping discount would seem quite profitable but not when we add a few more data points. Most retailers see a strong spike in both conversions and average order size around the holidays and events so mid-year average orders are probably lower than that $100 goal. Furthermore your new product may break margin rules and sell for an introductory price further lowering your ROI. Combine the two and that $40 buffer quickly turns into $30, $20, $10 and well you get the idea.

And of course it’s not just about seasonal events and margins. Offers change your order size and mix in many ways… free shipping with a $99 threshold may seem like a great way to get more orders but let’s build off the first example some more to see what really happens when you measure a promo gross. Assuming you already have a campaign that costs $0.50 per click, a 4.5% conversion rate and charge $8 for shipping for orders would have to move to over 5.5% or a full percentage point to cover the impact of the discount. On the other hand rolling out free shipping with a lower qualifier like $49 may drive your conversion rates through the roof but tank your average order size pushing your margins into the floor as you spend every free dime delivering a small order. In both cases your topline income would likely increase with more orders but again, more does not always mean more profit.

Of course most etailers have all this data at their disposal, it just requires going over to the product database here and there. But you already know what I’m going to say – and no that really doesn’t cut it. When you have to use multiple data sources things get overlooked or put off; a campaign that seems good on the surface doesn’t get delved into for a few days after which money’s been lost and decisions have been made. Only when the data is available in a central place does it truly become actionable and reliable and reliable is exactly what you need to make the next step decision.

So how do you do this? It’s actually fairly simple. Most enterprise reporting suites except secondary commerce metrics like product cost, shipping amount, tax and discounts all through their base tag structure with no need to build fancy import routines. More basic analytics may not tolerate secondary cost data but by computing the net result on your end before the data is put into a tag you can achieve the same result. Either way the analytic provider integration is pretty simple. What’s more complex is trying to bring raw product costs into your ecommerce system. In an ideal world this data should flow right out of your ERP/ Inventory system and to your site but that’s just not the reality for many businesses. A second solution is a simple update process to bulk modify records with raw prices at a regular interval (i.e. weekly). When even that isn’t available it gets down to manual updates and keeping up on them. No matter which integration phase you fit into it’s worth the effort and time to make it happen – and don’t stop half way, it’s better to use gross numbers than to have the wrong net figures anyways.

Once you have everything packaged together and can get that true top to bottom result set you’re ready to really rock and roll. Now instead of looking at campaigns against a big margin percentage you can start looking at both net and gross, pre-campaign cost and post and make decisions about what’s good for growth and what’s good for revenue and do so without waiting weeks to reanalyze every order in another tool.
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