In the 2013 Consumer Goods Technology Customer Management Solutions Guide, Steve Peppler, Flintfox Chief Product Officer, answered questions posed about the latest trends and challenges facing Consumer Goods manufacturers in the critical area of customer management: social media and mobile marketing, collaboration with retail partners, and Big Data.
Social networking changes the dynamics between consumers and Consumer Goods manufacturers. Now instead of bringing consumers in and asking them a set of detailed questions about their perceptions of your products, the consumer offers their opinions whether you like it or not, on social networks.
The opportunities from this new dynamic are enormous as now you have access to real time opinions and perceptions that you can proactively use to; target influencers who may not be your biggest consumers but whose opinion pulls a lot of weight, improve your product and messaging more proactively, immediately respond when negative or inaccurate opinions are expressed and refine your promotions so that they address a more finely tuned customer segment.
Creating timely snippets of information, coupons and promotional data allows for consumers to spread the word behind your campaigns to those that they believe are the most interested in your messages. What better way to spread your message than to have your best customers do it for you by targeting their friends, family and acquaintances.
The key is to try to find as many influencers as possible and have them spread the word, not because they are being paid to do so, but because they believe in the product and the message. Sincerity and targeted spreading of the word is a powerful medium.
CG manufacturers should strive to collaborate with retail partners by focusing on: the sharing of plans and data behind demand push/pull initiatives including new products, promotions and shelf management; working together to reduce supply related costs from financial/administrative processes to demand planning and inventory management; and always trying to ensure that all initiatives consider the impact on joint profitability.
One of the more powerful examples of collaboration that we see is the sharing of the impact of total financial returns expected to be earned by both partners with a promotion. This includes break-even and variance analysis as well as joint target setting and post event analysis. Developing trust through information sharing can lead to breakthroughs.
A beverage manufacturer we have worked with, leveraged their collaborative and trusted partner relationships to develop a much greater understanding of the demographics of the end purchasers of their product. It just so happened that the demographics of those purchasing in store differed from those that actually consumed the majority of the product sold. The purchasing demographics were known by the retailer while the consumption demographics were known by the manufacturer.
By sharing information they were jointly able to resize and repackage the product in such a way that both parties experienced an increase in sales and profitability.
Technologically the methodologies and tools available to collate, analyse and generate statistics out of “Big Data’ continues to improve daily. However, the sheer volume and disparity of data continues to outpace the advances in software and hardware. Data overload continues to make many companies’ big data plans sub-optimal at best or irrelevant at worst.
The way to address these issues continues to remain the same; focus on the data that relates the most appropriately to your business, engage all the stakeholders in the business not just analysts, limit the amount of results available to users via KPI’s (still giving them the ability to drill through further as necessary but as a second step), continually seek feedback from users and emphasize the importance of using data and facts as a culture across the organization.
The technological solutions chosen must take into account all of the above considerations before an investment is undertaken. A plan must be put into place to deal with the execution or tactical aspects of the data (e.g. using POS data to assist with proof of performance at retail) in addition to strategic solutions to consolidate data from different solutions into some form of business intelligence solution. A well thought out plan offers the best solution to leverage “Big Data”.