This is the final instalment in our 3-part blog series on Decision Science in B2B marketing. In the previous editions we defined Decision Science, why you should implement this approach in your B2B marketing strategy and what type of questions you can answer using Decision Science. This edition will focus on BNZSA’s newly established Decision Science department, why we decided to launch it, what the team does and what it looks like in practice.
Why did BNZSA launch a Decision Science practice?
BNZSA is committed to changing the demand generation industry and creating real opportunities for our clients which will convert to revenue. This objective is a core part of BNZSA’s DNA. Launching a Decision Science programme is an important new pillar of our infrastructure and will continually improve the quality of the leads we deliver to our clients.
Compared with a standard content syndication approach, our trademarked Warm HandoverTM process already has a 70% conversion rate and we’re investing further to improve on this. Our digital department was launched in 2020 with the aim of generating and nurturing pipelines for our clients. It also helped to collect better data on the buyer landscape. This has resulted in better quality opportunities for our clients.
Our new Decision Science practice will have clear campaign targets and objectives: supplying our clients with more and better quality Warm HandoversTM in less time. They will identify the actions required to achieve this objective and will then determine the insights and predictions we need to make to inform those actions. This will provide the data-based decision-making power that enables us to prioritise leads, understand with whom to talk, how and when.
What does BNZSA’s Decision Science team do?
Led by Angela Beresford, our team brings together multi-disciplinary skills to analyse all the information available to us in order to better understand business decisions – purchase decisions, and the marketing decisions needed to influence them. The skills and processes they use include data mining, business intelligence econometrics, machine learning, AI, foundation models and intent data. The output of these informs our actions.
A wide range of data is analysed to reach informed decisions. This includes customer data, second- and third-party data from the most reliable sources available and almost a decade’s worth of BNZSA’s own first party data. The best datasets are selected to address business challenges and are then processed using machine learning tools. This allows the team to extract immediate insights and build predictive models to identify the best leads, when and how to speak to them, and supply further insights that will support our clients through the sales process. .
This results in a powerful cycle which delivers better quality opportunities in less time, with fewer resources, whilst building a strong and sustainable pipeline.
Decision Science in Practice
Decision Science helps to define Ideal Customer Profiles (ICPs) and identify high potential opportunities more accurately. BNZSA implements five steps to deliver the necessary results:
- Information: Historical transactional data, company details, intent data, and enhanced contact history from our own data attributes.
- Intelligence: BNZSA define the ICP cased on companies with highest value, historic data, and market trends.
- Prediction: Predictive analytics are applied to select companies. Intent data implemented to highlight companies with the most immediate need, creating a specific target list of companies and contacts.
- Action: Our BDRs verify the need of the target list. Their script and communication style are adapted according to the customer profile.
- Measurement: We apply A/B/C testing to measure the impact of decision science vs intent data alone.
How can you get started with Decision Science?
If some of the above points resonate with your business operations and process and you want to explore the benefits of adding BNZSA Decision Science services to your marketing mix, please get in touch here. We’d love to hear from you and get you started on the road to Decision Science!
