Researching international millionaires

In presenting the findings of a study for the Swiss Bank UBS (www.ubs.com), Spring Research (www.springresearch.co.uk) delivered a one-day workshop that brought together over 30 stakeholders from Publicis Starcom (UBS’s media partner) and UBS teams. This grouping brought together a broad mix of experience and creativity. Spring wanted to hold the session in a climate where people felt confident about themselves and could work well with one another. It picked a comfortable, relaxed hotel in Zurich that allowed freedom of movement. Spring arrived early to dress the room with insights, images and stories of individuals who took part in the research as it wanted the environment to act as a stimulus. All workshop participants were given an HNWI (High Net Worth Individual, the type of participant the research project had focused upon) in advance of the session and asked to spend time thinking about this person’s needs, wants and desires. The workshop began with objectives for the day and a quick introduction on the state of the market. Spring then asked the workshop participants to really get into the minds of the HNWIs. Each was asked to get into character and then form into teams of eight people. In their teams, each individual was asked to introduce themselves before being interviewed by a journalist from ‘The Examiner’ (a fake national newspaper), who was tasked with finding out as much as possible about them and their colleagues. Each team was then asked to put together a ‘front-page story’ that would give the world the inside scoop on the audience’s lives. Each team was then asked to present its story to the rest of the group. As well as the individual consumer profiles, the teams put together verbatim comments and six short films to bring to life individuals and key themes. There was some reluctance about role playing before the event, but for many it ended up being the most rewarding element as they really got into the minds of the people they wanted most to reach. The level of involvement generated through this approach ensured greater ownership and commitment to the outcomes of the research from UBS and Publicis Starcom, and really helped introduce consumer insight directly into the ‘bloodstream’ of each organisation. It also enabled Spring to fast-track ideas as the right people were in attendance, so the session worked as an effective means of taking key decision makers on a journey that led to consensus and an agreed forward direction that was able to be acted on immediately.

Understanding the relationship between prices and sales at Premier Farnell

Premier Farnell (www.premierfarnell.com) markets and distributes electronic components and related industrial products from more than 3,000 suppliers. Premier Farnell’s proposition rests upon consistently reliable, appropriately priced deliveries. Working with specialist b2b research agency Circle Research (www.circle-research.com), Premier Farnell needed to answer the following questions:

• What is the relationship between delivery price and sales?

• What price premium do ‘value add’ elements of delivery justify (e.g. speed)?

• What is the optimum price for each delivery option – the point at which Premier Farnell can maximise profitability?

Circle was aware that Premier Farnell was going to make major commercial decisions on the basis of the research, so it needed to be highly reliable. Buying decisions involve a very complex and subtle relationship between price and benefit, and this relationship needed to be investigated if the research was to provide an accurate steer.
More than 2,000 customers globally were surveyed. Conjoint analysis (Chapter 26) was used to help understand the relationship between features, price and purchase behaviour. Different elements of the delivery proposition (including price) and the different levels at which these might be realistically set were identified, such as different delivery speeds. Using this information, a series of hypothetical delivery propositions were created, each with slightly different features and prices. These hypothetical offerings were then grouped into sets of three and customers were asked which one, if any, they would be most likely to buy under.
This was repeated several times until hundreds of potential combinations had been compared. Analysis of these data was then used to reveal the level of demand under different feature combinations and at different price points. This exercise revealed which aspects of the delivery proposition held greatest value and helped build an understanding of how changes in pricing would impact sales.