What drives trial levels?
There are numerous factors that will impact the percentage of consumers that trial a product, which marketers can influence and drive. Some of the factors to take into account include:
- Is this a product line extension? Product line extensions would generally have higher trial rates.
- Does this new product belong to a strong brand? Strong brand equity leads to higher trial rates.
- Is there a free sampling program in place? Free sampling will deliver higher trial rates (but much lower repeat/rebuy rates).
- Are there sales and/or trade promotions in place? If yes, then trial rates will be higher.
- Is the product promoted/sold by a sales team? A dedicated sales channel will achieve higher trial take up rates.
- Does the firm/brand have the ability to direct market the new product to their existing customer base? If yes, then the trial rate should be high.
- Is this a relatively low-cost product? If yes, then trial rates will be higher.
- Is the product supported by advertising and wide availability? Seeing the product being promoted and available in stores gives the consumers confidence that this is a product that provides value and is a quality – leading to increased trial take up.
- Is the product unique/differentiated? Products that offer a new benefit are more likely to have a higher trial take up than “me too” competitors.
- Does the product have a money back guarantee? Money back guarantees will reduce the perceived risk to the consumer, and lead to increased initial sales.
- Does the overall new product provide a high level of perceived value? The higher the perceived value to the end consumer, then the higher the likely initial trial percentage.
Trial rates should generally reduce over time
When a product is first released, it probably has its best chance at maximizing its trial rate. This is because the product is new and exciting and the potential consumers that see value in the product are more likely to purchase it early. This is particularly the case for product-line extensions and products under the support of strong brands.
Some lessor known brands might see an initial increase in trial rate in years 2 and 3, as positive word-of-mouth and greater product exposure gives more consumers the confidence to purchase the product. However, as indicated by the product life-cycle model, eventually the proportion of new/first-time customers will reduce.
The two trial scenarios described about are shown in the graph. Large brands will start higher, but then run off faster (but will generally always have a higher trial percentage). Whereas weaker brands will build for a while and then run off as well.