79% of Sales Organizations Face 'Difficulty in Data Utilization'. STRIX Officially Releases 'Conversational Dashboard' Function to Shift Sales Floor Decision-Making from Intuition to Fact-Based.

MEDIUM Corporation (Headquarters: Shibuya-ku, Tokyo; Representative Director: Shotaro Seki; hereinafter 'MEDIUM'), a leader in sales strategy DX, officially launched its new 'Conversational Dashboard' feature in April 2026. This feature allows users to query aggregated values on the dashboard using natural language, and an autonomous agent traces back through sales negotiation logs to provide evidence-based answers.

In response to sales organizations struggling with 'being overly reliant on individual intuition' and 'inability to make evidence-based sales decisions,' we released the 'Conversational Dashboard' function. Our goal is to create a world where data can be easily extracted without burden, and everyone can refer to data for sales decision-making.

Numbers are visible. Yet, sales still operate on intuition.

The Japanese sales scene is gradually reaching a state where data is 'possessed.' A HubSpot Japan survey shows that CRM adoption has reached 37.2% (Source: HubSpot Japan 'Survey on Sales Awareness and Actual Conditions in Japan 2025' *1), and including SFA and BI, many organizations now have some form of visualization platform.

Nevertheless, the same survey indicates that only 44.5% of organizations prioritize data in sales activities, while 55.5% still rely on intuition (Source: HubSpot Japan 'Survey on Sales Awareness and Actual Conditions in Japan 2024' *2).

79% of sales organizations face 'difficulties in data utilization,' with three main causes: personnel, management, and collaboration.

Why can't sales teams break free from 'intuition-based sales'? According to the same survey, 79% of sales organizations reported 'difficulties in data utilization' (*2). The breakdown includes a lack of personnel for data utilization (28.6%), inadequate data management within sales departments (28.1%), and undeveloped inter-departmental data collaboration (24.4%).

Furthermore, responses continued with sentiments like 'no awareness of data utilization' and 'can't visualize data utilization.'

Just looking at the numbers on a dashboard doesn't reveal the 'raw situation' of what's happening on the sales floor.

It is difficult to grasp the raw situation of what is happening on the sales floor by merely looking at the numbers displayed on a dashboard.

The dashboard might show '30 highly promising deals,' but what the manager needs next is the breakdown.

'Who exactly are these 30 deals?'

'Why were they judged as highly promising?'

'What's the next step to take?'

With current BI tools, to answer these questions, managers end up opening SFA for each deal and reading through negotiation memos one by one.

In response to this situation, we released the 'Conversational Dashboard' function, aiming to create a world where data can be easily extracted during daily sales operations, and everyone can refer to data for sales decision-making.

STRIX's 'Conversational Dashboard' function: AI agent explores and interprets full conversation logs, seamlessly converting quantitative to qualitative data.

With STRIX's dashboard, when you query the displayed aggregated values using natural language, an autonomous agent traces back through the underlying sales negotiation logs and provides evidence-based answers.

It can respond to questions that BI tools previously couldn't answer, such as 'Who are the 30 highly promising deals?', 'Which deals are stagnant?', and 'Where are the signs of loss risk?', by drilling down to primary information.

1. Deep dive into your own dashboard directly via chat.

By simply asking questions in chat about the aggregated values on STRIX's dashboard (e.g., deal certainty, pipeline, negotiation stage distribution), you can trace back to the breakdown of constituent deals and the context of individual deals. No effort is required to design new views in BI.

2. Seamlessly trace from aggregated values to primary information.

From 'Show me the 30 highly promising deals' to 'What are the loss risks for the 5 stagnant deals?', and even 'Summarize the customer's remarks in the relevant negotiation,' it provides answers across three layers: company, transaction, and negotiation logs.

The hassle of switching between BI and negotiation logs disappears, and the basis for decision-making is available on a single screen.

3. Reconfigure necessary data from necessary perspectives, on the spot.

You can reconfigure aggregations from any perspective, such as 담당자 (person in charge), 期間 (period), 業界 (industry), 金額帯 (price range), and 意思決定フェーズ (decision-making phase), directly from chat. The lead time previously incurred by requests to BI administrators or analysts is eliminated for business users.

4. Queries become organizational knowledge.

Chat history is accumulated in a reusable format as cross-organizational sales knowledge. Insights that tend to be individualized, such as 'signs of stagnation,' 'winning patterns,' and 'root causes of loss,' remain as organizational assets.

Benefits per use case are realized as time savings. Manager's pipeline.