Data intelligence service provided by 2BC




Helping you revolutionise business processes by utilising data.

Data intelligence service provided by 2BC

Data intelligence service provided by 2BC

Using a variety of data in strategy formulation and various selling processes has become an essential corporate activity. Analyzing large amounts of data such as sales results, and sales and marketing activities accurately show the actual state of your company and the future direction it should aim for. 2BC provides a wide range of support from examining strategies for data utilisation to examining campaigns based on analysis of actual conditions and results. By positioning data scientists inside 2BC, we support efficient analysis of big data, which also includes statistical approaches, and the application and transformation of these into business processes.

Utilisation of data intelligence in the sales
and marketing strategy stage.
Utilisation of data intelligence in the sales and marketing strategy stage.


The primary process is designing a strategy based on various information and hypotheses through a consultant in the strategic stage of sales and marketing. This is where 2BC provides support. In the analysis of current sales productivity, which includes market estimation and sales analysis by present customer attribute, purchasing trends of existing customers and sales process design, 2BC supports highly accurate fact-based strategy formulation by involving data scientists from this stage and clarifying the actual situation at the client based on a large amount of data.

Utilisation of data intelligence in the sales
and marketing implementation stage
Utilisation of data intelligence in the sales and marketing implementation stage


In this stage, it is essential to perform regular improvement activities by promptly feeding back results alongside the implementation strategy. For example, we analyse marketing-derived sales results with each campaign; analyse the correlation between high-volume activities, such as prospect website and e-mail activities, and outcomes; perform regular sales analysis by customer attributes; and measure changes in purchasing trends. Then, we support the realisation of more highly accurate campaigns based on current results by involving data scientists as members of accompanying support teams even if sales and marketing are inserted into the stage where campaigns are being implemented, such as performing sales productivity analysis in the sales process.

Applied measures based on utilisation
of data intelligence
Applied measures based on utilisation of data intelligence


Even in B2B, many companies are being forced to change their business models, including digital transformation, due to rapid market changes, such as diversification of purchaser buying habits and declining workforces. Beyond sales and marketing activities with high levels of implementation and degrees of maturity, for example, the following can be seen: account selection automation based on forecasts of expected purchasing value by means of AI, automation of measures based on real-time data collection for sales and marketing activities, and the building of intelligent data platforms that support such activities. Having the knowledge and a track record even for such highly progressive initiatives, 2BC’s data scientists will co-create the future with our clients.

2BC’s data analysis environment (example)

In addition to being able to build analysis platforms, such as an Anaconda analysis environment, R, or SPSS with SAS or Python languages, into a 2BC or client environment, we can also handle either a very solid stand-alone, on-premise environment or a highly flexible cloud environment.

Actual examples of data intelligence

2BC provides a broad range of support from examining data utilization measures to campaign planning and implementation based on actual analysis and analytical results.
By positioning data scientists inside 2BC, we support application and transformation of business processes with efficient analysis of big data, which includes statistical approaches, and we introduce specific data intelligence projects.

Utilisation of data intelligence in the sales and marketing strategy stage
Examples of actual results:

E-mail nurturing based on market potential estimation and order forecasts
We analysed order performance by customer product category, and this led to us devising a plan for estimation of SAM and TAM, and a sales strategy from market scale and share. In addition, we built an order forecasting program by customer units, which led to the implementation of e-mail nurturing based on order probability.
Setting business goals
While combining multiple data, we determined important business indicators and KPIs, and from then on we collected and calculated data in real time. We also built a PDCA cycle by evaluating KPI attainment levels, which lead to quick implementation of campaigns.

Utilisation of data intelligence in the sales and marketing implementation stage
Examples of actual results

Design of engagement programs
As a marketing activity for prospective customers, we analysed active and passive customer behaviour and reactions to campaigns by customer clusters. Then, we designed an engagement program by target with optimal targets. In particular, we performed scoring and set handoff thresholds based on Web browsing behaviour for each destination.
Optimisation of marketing campaigns based on analysis of customer behaviour in chronological order
We analysed reactions to our campaigns in chronological order of months and years for prospective customers. As a result of providing optimally timed campaigns for each customer, we furthered the promotion of MQL and SAL.
Forecasting and classification by multivariate analysis
We performed multiple regression analysis and discriminant analysis, factor analysis, cluster analysis, etc. for sales data and customer data. Then, we searched for leading causes of fluctuations in sales, forecasted future sales, and built customer segments.
Marketing research
We conducted questionnaire surveys from prior to building cluster model questionnaire designs and hypothesis testing, and then we ascertained needs trends and social receptivity by performing tests of cross-tabulation and aggregate values, and deriving cluster groups. Qualitative information was also added by conducting interview surveys as needed.

Data Intelligence Application Measures
Examples of actual results

Future business and service forecasts
We adjusted coefficients from qualitative information while using statistical techniques, and made future business and service forecasts. Besides, we built marketing mix models and reflected the effects of campaigns such as advertising in our forecasts.
AI utilisation consulting
In the fields of software, cloud services, applications and robotics, we provided business consulting aimed at introduction of artificial intelligence. We carried out consulting focused on the impact of utilising artificial intelligence, and its effect on company business and operations.