Personal Selling's Effect on Sales

ConversionAlbers, S.; Mantrala, M.K.; Sridhar, S. · 2010Journal of Marketing Research
Topicspersonal selling·sales force effectiveness·product life cycle·lingering sales effects·pharmaceutical detailing·sales benchmark

A sales VP is defending next year's field headcount, and every study she cites gives a different read on how much selling effort actually moves sales. Before she anchors the budget on any one number, she needs a benchmark she can trust and a sense of where the number quietly changes based on the product and the market. This finding gives her both: a stable in-period response rate, evidence that the payoff continues well beyond the period it's spent, and clear conditions under which selling effort works harder or softer.

A dollar of selling effort keeps paying off well after the quarter it's spent.

Pooling many studies of sales-force effort, a 1% increase in selling effort raises sales by about 0.3% in that same period, and the effect is persistent: about three-quarters of it is still present the next period rather than fading. (The studies stop short of adding that persistence into a single long-run number.) The payoff is uneven, though: it runs much stronger for new products, in Europe, and outside pharmaceutical detailing.

Data chart

Where selling effort works hardest

New products0.54General B2B selling0.50Europe0.43US0.32Pharmaceutical detailing0.27Mature products0.27

The same dollar of selling effort pays off very differently depending on the product and the market.

Action guide

  1. Anchor sales-response planning on a roughly 0.3% sales lift per 1% of selling effort, in the same period.Treat this as the credible planning benchmark rather than higher figures that skip adjustments for how the study was run.
  2. Don't judge selling effort on its first-period results alone.The effect is persistent, about three-quarters of it still present the next period, so first-period sales understate its full contribution. Set a high persistence assumption in your sales-response model; this is a persistence rate, not an ROI or payback figure.
  3. Weight new-product launches more heavily in selling-effort allocation.Responsiveness runs about twice as high for early-life products as for mature ones, so effort shifted toward launches earns more.
  4. Deploy relatively more selling effort in Europe than in the US when margins and current sales are comparable.European markets show a meaningfully stronger response to added effort.
  5. Treat pharmaceutical detailing as a lower-payoff lever than general B2B selling, and test complementary channels for mature drug portfolios.Detailing responds less than selling in other business-to-business settings.
  6. Before comparing two studies' numbers, check how each was built.Differences in modeling approach, not real market differences, explain much of the spread between reported figures.

Evidence

  • For every 1% more selling effort, sales rise about 0.3% in that same period, after adjusting for how the underlying studies were run.
  • The effect is persistent: about three-quarters of it is still present the next period, so selling keeps working after the spend — though the research stops short of summing that into one long-run figure.
  • Selling effort works about twice as hard on newer products as on mature ones.
  • Selling effort moves sales meaningfully more in Europe than in the US.
  • Pharmaceutical detailing responds less than general business-to-business selling.
  • The size of the reported number depends heavily on how the underlying study was built, so raw comparisons across studies can mislead.

Key takeaway

Selling effort lifts sales about 0.3% per 1% spent, keeps paying off afterward, and pays off most on new products and in Europe.

Source

Albers, S., Mantrala, M. K., & Sridhar, S. (2010). Personal selling elasticities: A meta-analysis. Journal of Marketing Research, 47(5), 840–853. https://doi.org/10.1509/jmkr.47.5.840

Read the paper ↗

Evidence strength: Strong, pooling over 500 sales-responsiveness (elasticity) estimates from 75 econometric studies across 88 data sets, heavily weighted toward pharmaceutical and defense-recruiting settings in the US and Western Europe. Generalizes most confidently to those settings and less confidently to consumer retail selling, non-Western markets, or future periods.