Will my trnd WOM Campaign Drive Sales?

trnd Word-­‐of-­‐Mouth Marke0ng “Will my trnd WOM Campaign Drive Sales?”
The direct answer is easy: Yes. It will, absolutely. That’s why we’re doing this! The combina<on of real product experiences provided to thousands of people and high engagement levels has been proven <me and <me again to posi<vely impact sales. So the ques<on is not if it will or if it won’t. The ques<on is: can you measure the impact? And that’s a liEle more difficult to answer. When these non-­‐users are asked aPer the WOM experience if they now intend to buy the product, large parts of them say that they will or already did: WOM Impact on WOM Receivers: What happens
when consumers
hear WOM?
“Are you going to buy the product?“ “I may in the future!“ “I definitely will.“ 100% 71% 29% New users 50% Exis0ng users That depends. WOM marke0ng effects can only be made visible if other factors don‘t play against it. A wide range of marke0ng factors play decisive roles, and these are factors that trnd cannot control: Product Place 36% “I already did.“ Where is the product available? How prominently visible? Percentage of distribu0on achieved? Special placements What is compe00on doing in-­‐store? How many distribu0on chains are covered? Etc. “No, not interested.“ A trnd campaign reaches ... So I’ll definitely see
a Sales Uplift?
Packaging? Uniqueness? Key benefit Innova0on? Product experience? Added value? Etc. 44% We know from research – conducted by ifwom ins0tute, Berlin* – that WOM from trnd campaigns is highly convincing. ifwom have analysed responses from 22,605 receivers of word of mouth from 15 trnd WOM campaigns. The results show us that trnd campaigns reach a surprisingly large share of previous non-­‐users: Market Effects: Price How expensive vs. average? How expensive vs. value impression? Price promo0ons? Compe00ve price promo0ons? Etc. 13% 7% Answers of new users 0% trnd AG – The European Word-­‐of-­‐Mouth Marke0ng leader – Web: www.trnd.com/company Promo<on Size of WOM campaign vs. popula0on? Number of WOM triggers? Timeliness of shipment? What other ad campaigns are running at the same 0me? Is compe00on adver0sing heavily? Etc. *ifwom is a research ins0tute based in Berlin that specialises in researching the impact of WOM campaigns and providing qualita0ve WOM analysis. More at: www.ifwom.com trnd Word-­‐of-­‐Mouth Marke0ng – March 2012 Examples: Measurement Case Studies from 2011.
As we have seen on the previous page, excited par<cipants in trnd WOM campaigns can create remarkable effects among those they speak with. However, that alone cannot guarantee a visible effect. Only if other marke<ng factors are not crea<ng a nega<ve impact, a trnd campaign’s effects on sales can be shown. Here are two examples, one from trnd Germany and one from trnd Hungary. Vita Cola is a regional cola brand, only available in parts of Germany. As a result, our 5,000 campaign par0cipants were crea0ng their WOM effects in a popula0on of around 10 million inhabitants. In other words, we had a concentra0on of 0,05% WOM connectors. The hero product was renamed “PUR“ at the beginning of 2011. The trnd campaign was carried out in the summer, two months aPer an outdoor ad campaign. There were no other ad ini0a0ves. Sales impact measures are based on Nielsen data over three years, our modeling includes weather data, sales promo0ons, all adver0sing, and WOM. The 3-­‐year-­‐
model has a fit (R2) of 96.4%**: trnd Germany, drinks category: trnd campaign Sensodyne
Pronamel
campaign
+29.6%
trnd campaign +23.7%
in A
2011 model without trnd ugust* + 21.5% In our modelling, based on two years of Nielsen data, we found that price changes explained a large percentage of sales fluctua0ons. When we added informa0on about an extraordinary beauty promo0on in the summer of 2011, and the trnd campaign, the model had a remarkable fit of 99,8% (R2)**: trnd Hungary, dental care category: Vita Cola Pur,
Renaming
campaign
2011 model without trnd 2011 with trnd Sensodyne Pronamel is a toothpaste brand by GlaxoSmithKline, the product is specifically designed to help protect teeth from the effects of acid erosion. We ran a campaign with 1,000 par0cipants in Hungary, achieving a concen-­‐
tra0on of 0,01% connectors in the popula0on. in Octobe
r* + 23.3% 2011 with trnd + 29.6% + 23.7% model measures only short term effect Jan Feb Mar Apr May Jun Jul Aug Sep Okt model measures only short term effect Nov Dec trnd AG – The European Word-­‐of-­‐Mouth Marke0ng leader – Web: www.trnd.com/company Jan Feb Mar Apr May Jun Jul Aug Sep Okt Nov Dec * Please note that both models do not include long-­‐term effects – these calcula0ons can only assess the direct effect, not the long-­‐term impact on par0cipants and WOM receivers. ** Data: Nielsen. Modeling: trnd Research and ESCP Berlin. trnd Word-­‐of-­‐Mouth Marke0ng – August 2012 Examples: Researching Sales Impact in 2012.
In 2012, we undertook two very exci<ng sales impact analyses: Together with our client Tchibo, we analyzed the effects of a WOM campaign on visitor numbers and sales in its Budapest retail stores. And we ran a large-­‐scale sales data analysis, gauging the effect of WOM marke<ng across a range of 11 different WOM campaigns that we had conducted over the past several years, based on mul<-­‐year Nielsen sales data. Tchibo wanted to drive people to their bricks-­‐and-­‐mortar Tchibo shops in Budapest. The campaign employed a combina0on of pre-­‐
buzz, dialogue, and post-­‐buzz modules. (The post-­‐buzz module was focussed on the Tchibo online shop.). 1,500 par0cipants were turned into Tchibo store ambassadors, invi0ng friends and family to experience the Tchibo stores. The modeling was based on Tchibo’s own extremely detailed store traffic informa0on, and on their daily purchase/sales data. The model included shopping seasonali0es (incl. Christmas), weather, varia0on in product range amrac0veness, new store openings, and other marke0ng ini0a0ves. The model fit was very good – depending on the dependent variable, it lay between R2=86.3 and R2=92.0.* In order to assess an average effect that a trnd WOM campaign can have, researchers at trnd and at ESCP business school (Berlin) conducted a mul0-­‐product 0me series analysis.* trnd Germany, 11 campaign sales analysis: trnd Hungary, retail campaign: Tchibo Stores,
Retail campaign
€ 3.93 of revenue
generated per €
spent on campaign
To do this, 3 years of Niesen sales data rela0ng to 11 campaigns and 8 different products were analyzed.** The objec0ve was to extract a generalized WOM campaign effect out of these 11 data sets and build a model that is able to show this effect. •  On average, € 3.93 revenue generated per € invested. 32541 Addi0onal visits In revenue terms, the campaign returned twice its costs, it led to 6% addi<onal revenue for the whole quarter. 8407 Addi0onal purchases 0 5000 •  9 out of 11 campaigns led to an immediate posi<ve pay-­‐out. 10000 15000 20000 25000 30000 •  4 out of 11 campaigns led to an immediate pay-­‐out of more than € 5 per € invested. •  3 out of 11 campaigns had an immediate pay-­‐out of more than 10. •  In 9 out of 11 campaigns, the pay-­‐out per € invested was higher than the pay-­‐out achieved through tradi<onal adver<sing. 35000 trnd AG – The European Word-­‐of-­‐Mouth Marke0ng leader – Web: www.trnd.com/company * Please note that both models do not include long-­‐term effects – these calcula0ons can only assess the direct effect, not the long-­‐term impact on par0cipants and WOM receivers. ** Data: Nielsen. Modeling: trnd Research and ESCP Berlin.