E-commerce Insights: Multichannel Planning Is a Complex Endeavor
Scratching your head over the interaction between your online and offline marketing efforts? Not sure how much to advertise online? Unclear of the true impact of your catalog mailings? You’re not alone. This column won’t completely solve these puzzles, but it’ll offer some relevant ideas.
How Much to Advertise
First, assume you’ve already established your high-level financial goals, either for your online program or for the business as a whole. Such goals should be specific, numeric and time-based. Be sure the whole team understands and buys into these goals, and works toward meeting them each week. Typical goals are profit-and-loss-based, and include a revenue and an earnings component. Rapidly growing companies also may have a cash flow goal.
Build a planning P&L statement based on these goals. Usually, a marketing P&L stops at marketing contribution since marketing typically isn’t held accountable for fixed costs and overhead. If your margin doesn’t vary greatly across your marketing efforts, this planning P&L effectively helps you understand the trade-off between marketing expense and resulting sales.
I find it helpful to discuss sales in terms of absolute dollars (volume) and marketing expense in terms of a percentage of net sales (efficiency). Expressed as a percentage of sales, the marketing spend becomes the advertising-to-sales ratio (A/S). Don’t allow different departments to use different assumptions for margin or variable cost (e.g., do vendor co-op funds reduce marketing expense, or rather reduce cost of goods?). Task your finance team with ensuring marketing and merchandising use consistent numbers.
Your programs in aggregate should meet your efficiency goals. Allow your marketing team leeway to cross-subsidize programs within the portfolio at their discretion. If you require every program to meet your target efficiency, the portfolio as a whole would be too efficient, leaving potential revenue on the table (see Figure 1 below). Dig deep and make sure your team can explain which laggard programs they’re propping up and why. Good explanations are “testing new opportunities,” “trading some efficiency for increased volume” or “strategic considerations.” Bad explanations are, “We don’t know,” or, “We’ve always done it that way.”
This perspective applies to list rentals and paid search keywords:
• require the portfolio to “work” in aggregate,
• allow your managers discretion in the portfolio, and
• inspect, occasionally, disaggregated performance by list or keyword.
To determine the trade-off curve between advertising and resulting sales, turn to historic data or construct controlled tests. Earmark 5 percent of your marketing budget for testing brand new opportunities. Budget another 5 percent to test “over-marketing” of existing channels: small selects from marginal lists, small ad spends on marginally converting keywords, mailing a bit below your cutoff to your buyer file, and so on. Modest, ongoing over-marketing lets you collect critical data on the shape of your advertising vs. sales trade-off curve.
The advertising-to-sales trade-off curve typically isn’t smooth. You either take a list or keyword, or you don’t. And it often has a very steep cliff. That means, once you’ve bought the good stuff, the quality plummets, and additional sales come at a huge ad cost.
For modeling purposes, it can be helpful to assume this trade-off curve is smooth for small changes. The “square root rule” takes this approach, stating that sales increase linearly with the square root of advertising. It’s a wrong assumption for large changes, but a useful approximation for small ones.
In brief, the square root function:
• shows decreasing returns to scale,
• is internally consistent, and
• offers theoretical properties.
At www.rimmkaufman.com/squarerootrule, I’ve placed an Excel spreadsheet which uses the square root rule to model the potential effect of slight increases or slight decreases in your advertising spend, as well as suggested the advertising level which optimizes contribution (see Figure 2 below).
One rule of thumb that emerges from the square root assumption is that marketers maximize their marketing contribution dollars by spending half of their effective margin on advertising. For example, a marketeter selling products with 45 percent cost of goods sold and 12 percent other variable expenses should aim for an advertising-to-sales ratio of (1⁄2) x (1 - .45 - .12), or 21.5 percent.
Acquisition vs. Retention
Catalogers traditionally have partitioned their marketing efforts into acquisition and retention programs. Many firms ran their acquisition efforts to breakeven or below, satisfied to bring new buyers onto the file without profit for the lifetime value of the customers and for the top-line benefit. When marketing to their active buyer file, catalog firms would only mail their books to fresh, highly profitable segments, as the resulting orders had to cover not only the cost of marketing to active buyers, but also of marketing to prospects, covering overhead and generating overall profit.
The tremendous economic importance of their active buyer files caused many catalogers to overestimate the loyalty of these customers. The rise of e-commerce and paid search totally has changed the concept of customer loyalty. In years past, a retailer’s catalog might be the only exposure a household received to merchandise in a particular category. No longer. The Internet puts every SKU in front of every consumer. In the age of the Web and Wal-Mart, customer loyalty is hard-won, rare and easily lost.
In paid search, the traditional catalog paradigm of acquisition vs. retention is replaced by non-brand vs. brand search. When searchers find you online using your brand name (e.g., “Lands’ End shirt,” “Harry and David,” “Chase credit card”), they’re using the search engine like a White Pages. For this search, they’ve exhibited enough loyalty to find your site by name — regardless of whether they’re on your active buyer file or not. In contrast, searchers who find you online though nonbrand search (e.g., “men’s oxford shirt,” “fruit basket gift,” “rewards credit card”) are using the search engine like a Yellow Pages. They’re comparing you to your competitors. This order is “in play” regardless of whether that customer is or isn’t on your active buyer file.
Just as catalogers mail their most recent buyers, online retailers should buy search clicks on brand terms. They’re low-cost and high-converting, although the resulting sales largely are non-incremental. While you receive lower efficiency on nonbrand paid search ads — you need to pay a greater share of revenue in advertising — more of these orders are incremental, capturing marketshare from competition.
Order Allocation Rules
In the past, when households received your marketing messages less frequently, allocating orders to customers was simple: Give the last marketing communication credit for the order. This rule doesn’t work anymore, as our messages barrage potential buyers in overlapping torrents. Perhaps the last touch before the order was an e-mail, but the prospect received a catalog the week before. Or the last touch was an e-mail, but the e-mail sign-up was driven by a paid click.
The irony is that increased ability to track orders and marketing due to the Web and technology advancements has cut the true understanding of response. The multichannel order allocation problem is far from solved. While the industry struggles to develop accurate methods for multichannel planning, try to expose and discuss your current order allocation rules. Don’t bury these assumptions deep in your business logic. Bring them to the forefront to determine if your strategic models are sensitive to these assumptions. They will be, and that’s terrifying. The “right” way to determine the true marketing drivers of customer behavior are ongoing, cross-channel, hold-out tests, which are difficult to design and implement, slow, and costly.
Multichannel has changed direct marketing’s physics. Search has reduced “customer loyalty via ignorance.” Simple rules of housefile vs. acquisition economics aren’t so simple. Order allocation rules matter, more than you think.
Track sales and marketing costs at the customer level across channels. Differentiate sales from brand vs. nonbrand search phrases. Monitor efficiency just above and below your advertising cut-off, and start hold-out testing to determine your true marketing drivers of behavior.
Alan Rimm-Kaufman is president of the Rimm-Kaufman Group, a paid search marketing firm serving catalogers and other direct marketers. You can reach him via his blog at www.rimmkaufman.com/rkgblog.