Whether it’s a global consultancy or a local small business, everyone seems to talk about the trending topics digitisation and automation. Future visions and possibilities are numerous and seem unlimited. Already now data streams determine and optimise our behaviour in many areas – at least that’s how it seems at first glance – and make our lives easier. Also in the B2B sector the influence of data becomes more and more relevant, especially for the target of better understanding different types of customers and their respective needs.
- Should B2B companies implement data collection and analysis solutions as soon as possible to join the trend?
It depends on the current level of digitisation of the company and the solutions that are already in place. Introducing new systems is not always needed to meet the needs of digitisation. Many B2B companies lack the understanding of which data points should be the focus of marketing and sales activities and how these data points can be collected and used.
To create clarity about which data is needed for campaigns and use cases, companies often conduct a persona analysis first. The persona analysis is used as a qualitative basis for further quantitative investigations. This article explains how such an analysis can look like and what are the important thoughts in the process.
Data Collection for Customer Analysis
Data is relevant in many areas of a company, but this article will focus mainly on those areas that are in direct contact with customers: Sales and Marketing. Both departments need a good understanding of the customer and their needs.
Collecting new data for customer analysis should not be the first step in the process. Instead, it is advisable to first gather existing information and understand their relevance for understanding the customer. A time-limited, cross-functional and cross-competence discovery phase at the beginning of a project is recommended to bring together all key stakeholders, gather relevant information, define goals, and plan the necessary next steps.
A major challenge here is that much of the insight and experience about the customer base is considered tacit knowledge, meaning that it exists only in the minds of employees and in most cases has not yet been collected and written down. In order to expose these experiences a well-proven format that helps is a personal interview or a group discussion. Relevant discussion partners are all those who are in daily or frequent contact with customers – sales and customer service – or in the best case even the customers themselves.
The goal of these discussions is to collect information that makes the customer “approachable“ and allows the gathered information to be summarised into persona profiles. The translation of the information on the personas into data points is the next step in the process and makes the customer tangible. Each persona should have some critical characteristics that allow us to assign customers to a specific persona category. Only when the persona analysis is completed and critical data categories and data points are defined, the collection of (new) data becomes relevant.
But what is a Buyer Persona?
A (buyer) persona is a fictitious person profile that attempts to make typical target customer segments more understandable and tangible through a detailed description. Instead of talking about a “very digital” customer segment, this segment should be represented by a fictitious person and given a name. The persona is almost like the main character from a novel, as it is endowed with characteristics and a background story. Depending on the product or service, the profile can include demographic, personal, as well as professional aspects. The goals and needs of this “main character” are a central component of the persona.
In future we will no longer be talking about “digital customers“ but, for example, about Darwin, 25-30 years old, single, living in a shared apartment in a big city, his cell phone always at hand and therefore “digital-first”. He works in the purchase department and is responsible for the whole purchase process. He prefers fast decision-making processes with clearly structured data and can be reached by e-mail at any time. Face-to-face meetings are a waste of time for him.
This is what – in a nutshell – a buyer persona profile might look like. The knowledge about the persona helps to align communication for the customer with his interests and preferences.
Can every single customer actually be assigned to such a profile? Probably not, because humans are too individual. However, personas can map a large percentage of customers relatively accurately and at least highlight the significant differences. Creating a persona is comparable to formulating a research hypothesis that must be validated using data and analyses.
B2B Buying Persona
Since customers differ, a persona analysis will result in a different number of persona profiles, which can be distinguished on the one hand by demographics (e.g. age, marital status) and on the other hand by their needs, goals, areas of interest, and challenges. In the B2B sector another important aspect plays an important role, namely the role or position in the company and the associated decision-making competence. This is so relevant since B2B persona profiles differ highly along the buying process and can usually be broken down into six to seven different types.
A common misconception of the sales teams is that they are often convinced of already knowing the customers and all the related decision and buying processes but this is rarely actually the case. However, suppose the core personas along the buying process are known and understood. In that case, they can be addressed individually along the buying cycle, and the whole process can thereby be accelerated significantly.
Information relevant for the people in the purchasing department (e.g. price list) may be of secondary interest to the technical decision-maker. Nevertheless, both should be contacted and targeted with respective relevant content.
So When Does Real Data Become Relevant?
After the qualitative findings from interviews and workshops have been translated into buyer personas, the personas as such already offer added value. They provide an aligned picture of the target customers that helps in internal discussions and target settings.
The next step is to convert the personas into data points. From the persona description, “25-30 years old,” the data point “Age group by year of birth” or “Generation Y” could be derived accordingly. Behavioural data points such as preferred communication channels or online behaviour are also interesting and can be tracked by analysing the web behaviour of the customer. Data sources for the tracking of the relevant data points can come from internal systems, so-called zero and first-party data, but also be enriched by 3rd party data.
This 3rd party data might come through marketing automation or analytics tools such as Google Analytics.
Real customer data will validate personas, enrich them, and approximate the internal customer database to persona profiles. The personas are therefore not necessarily finalised after the qualitative interviews but can further be verified and adapted over time. Technical solutions offer the possibility for tracking and analysing the data points and pave the way to a data-driven business model.
For the persona example “Darwin“ that we used previously, we can now define the critical data points to track customers similar to him. So a customer who is <30 years old, lives in a big city, and uses digital media (e.g. app, social media) with above–average frequency could likewise be assigned to the persona “Darwin.“ If we also know that the persona is located in the purchase department, we can adapt to his needs and limit communication to topics relevant to purchasers.
Personas and Data Go Hand in Hand
In summary, digital solutions provide deeper insights to understand customers and better meet their needs. For this purpose, customer data should be reviewed qualitatively as well as quantitatively to promote a customer–centric focus. Persona profiling can be an optimal first step to (re)align digital solutions and reveal missing data points that can be either covered by zero or first party data, or be covered through additional 3rd party data. The persona analysis will detect the customer types that are currently being served and how they can be identified in the company’s own systems and databases. Such preliminary work will already have a direct impact on the efficiency of the marketing budget by creating the basis for more advanced quantitative optimisations such as A/B tests, progressive profiling, or click tests.
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