The new B2B consumer - The ReAD Group
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This document discusses strategies for engaging B2B consumers. It notes that B2B buyers now research online like consumers, so B2B companies need to blend B2C and B2B engagement approaches. Specifically, companies should target the right audience by using consumer data to understand behaviors and interests. Two examples are provided where companies successfully drove desired behaviors and outcomes through targeted campaigns that creatively engaged specific audience segments.
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The new B2B consumer - The ReAD Group
- 1. The New B2b Consumer June 2012
- 2. Agenda Traditional engagement strategies Targeting the UK business population The emergence of the Prosumer The benefits of blending Choosing and matching the right consumer data Real world examples Driving the creative and media mix Rewarding behaviour Summary
- 3. B2b sales engagement stack High Value Corporate • Senior level engagement • Business-wide solutions Enterprise • Account management • Single department SME/SoHo • Marketing lead engagement Low Value • Tele-supported
- 5. Targeting the right audience SoHo/SME Enterprise/Corporate
- 6. B2c blending Such a large market segment needs effective targeting Adds a new layer of knowledge Help inform social media strategy SoHo/SME purchases not always commercially driven
- 7. The emergence of the Prosumer Technology is driving a new decision making process A threat Buyers research 10.8 reference sources 79% of buyers use their smartphone to reference products & services 54% comparison shop Sales engagement is becoming less relevant Loss of brand control Reference: Google ZMOT research
- 9. The emergence of the Prosumer Technology is driving a new decision making process An opportunity Opportunity to listen and engage early Nurture prospects Multiple channel engagement New ways to transact Reference: Google ZMOT research
- 11. Choosing the right consumer data • Off-the-shelf robust solution Geo-dems • Postcode level can provide misleading outcomes • Household and individual level data Lifestyle • Good insight into household make-up and interests • Ideal for trigger based products/services Transactional • Ensure sufficient coverage to develop robust model
- 12. Define the outcome An effective model needs a clearly defined objective Audit your existing database Remove non-marketable records and PAF check Match criteria Agree type of match i.e. postcode, household, or individual Test model Ensure match levels are sufficient to produce a robust model Run test campaigns
- 13. Campaign deployment Creative Driving behaviour Van Insurance Loyalty
- 14. Commercial Insurance – Van drivers Key Cluster Demographics Household income £30,000- £40,000 Trade/craftsman Average credit risk Pay for insurance in full Interests include fishing, football and camping Subscribes to Sky More likely to read The Mirror, Daily Star or Sun on a daily basis
- 15. Commercial Insurance – Acquisition
- 16. Commercial Insurance – Outcome
- 17. Rewarding behaviour – Trade Wholesalers Key Cluster Demographics Home owner Married with two dependants under 10 Above average credit risk Interests include betting, bingo, days out, cinema & football More likely to read The People Sunday Express
- 20. Summary
Hinweis der Redaktion
- Typical sales engagement – marketing needed at lower level
- Challenge biggest market lack of info 1-10,11-250,250-999, 1000
- Selection criteria high low – Corp and Enterprise covered, SME/SoHo lack of data, insight and low ROI BIGGEST MARKET LEAST COVERAGE
- Set the scene to drive new communication that encompasses social drive decisions – clarity
- Later walk through a number of examples. Consider types of data and its use
- Set the scene to drive new communication that encompasses social drive decisions – clarity Define the outcome Agree matching criteria i.e. individual, household or postcode level Test data sources for match levels to your own file – low level matching will lead to poor model
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