why is salesforce stock dropping - 2-3 bullets

Calling: search_ticker - query="Salesforce"

Calling: exa_web_search - post_search_concerns="I need to find recent news or market analysis explaining why Salesforce stock might be dropping.", queries=["Salesforce CRM stock dropping reasons June 2026", "Why is Salesforce stock down recently 2026"]

Salesforce (CRM) stock has experienced recent volatility and downward pressure due to a combination of market sentiment and company-specific factors:

  • Disappointing Forward Guidance: While Salesforce reported strong fiscal first-quarter earnings that beat consensus estimates, the company's forward-looking revenue guidance for the full fiscal year 2027 fell short of some analyst expectations. This created investor anxiety that near-term growth might be decelerating despite the strong quarter.
  • Structural Concerns Over AI: There is growing investor fear regarding a "structural reset" of the software industry. Salesforce’s transition from a traditional per-seat licensing model to a consumption-based model (via its "Agentforce" AI platform) has raised concerns that AI agents could ultimately cannibalize legacy revenue by replacing the human users who historically paid for those seats.
  • Profit-Taking and Analyst Revisions: Following a significant rally immediately after the earnings report—fueled by the positive results and a large capital return program—the stock faced heavy profit-taking. This was compounded by several Wall Street firms trimming their price targets, signaling a more cautious near-term outlook as the market digests the company's transition to an AI-agent-focused model.

max 30 words - what was the change in guidance?

Salesforce’s full-year fiscal 2027 revenue guidance fell slightly short of analyst expectations, fueling investor concerns about potential growth deceleration despite the company beating first-quarter earnings estimates.

give numbers

Salesforce provided the following guidance for fiscal year 2027:

  • Full-Year Revenue: Projected at $45.9 billion to $46.2 billion.
  • Q2 Revenue: Forecasted at $11.27 billion to $11.35 billion.

Investors had expected slightly higher targets.

IS Fy26 for salesfroce finished? If yes - what was full year and Q2 revenue in fy26

Calling: load - metrics=["total_revenue"], tickers=["CRM"] DataFrame 140 OK crm_fundamentals (101 rows)

Calling: compute - dataframe_ids=[140], code="result = df_140[(df_140['date'] == '2026-01-31') & (df_140['period_type'] == 'annual') | (df_140['date'] == '2025-07-31') & (df_140['period_type'] == 'quarterly')]" DataFrame 141 OK result_141 (2 rows)

Yes, Salesforce's fiscal year 2026 (FY26) is complete (it ended January 31, 2026).

  • Full-Year FY26 Revenue: $41.53 billion
  • Q2 FY26 Revenue: $10.24 billion

Can you make a chart with salesforce stock price earnings ratio last 5 years

Calling: load - metrics=["close", "trailing_pe"], tickers=["CRM"], start_date="2021-06-08"

DataFrame 142 OK crm_price (1256 rows, cols: ticker, date, close)
DataFrame 143 OK crm_overview (1 rows, cols: ticker, date, trailing_pe)

Calling: load - start_date="2021-06-08", tickers=["CRM"], metrics=["eps_reported"] DataFrame 144 OK crm_fundamentals_131512_72e3fe (111 rows)

Calling: compute - code="df_142['date'] = pd.to_datetime(df_142['date'])\ndf_144['date'] = pd.to_datetime(df_144['date'])\ndf_144 = df_144[df_144['period_type'] == 'quarterly']\nmerged = pd.merge_asof(df_142.sort_values('date'), df_144.sort_values('date'), on='date', by='ticker', direction='backward')\nmerged['pe_ratio'] = merged['close'] / merged['eps_reported']\nresult = merged[['ticker', 'date', 'pe_ratio']]", dataframe_ids=[142, 144] DataFrame 145 OK result_145 (1256 rows)

Calling: show_chart - series=["pe_ratio"], dataframe_id=145, x="date", title="Salesforce (CRM) Price-to-Earnings Ratio (Last 5 Years)" Blob 63 DataFrame 145 OK result_145 (1256 rows)

Data MAX

The chart above displays the Price-to-Earnings (P/E) ratio for Salesforce (CRM) over the last five years, calculated using quarterly earnings reports.

I dont understand the latest numbers - how is iit near 40/50s. Can you check with net income, and market cap?

Calling: load - tickers=["CRM"], metrics=["market_cap", "trailing_pe", "eps"] DataFrame 146 OK crm_overview_131607_bac719 (1 rows)

The confusion stems from a technical error in my previous chart calculation: I used quarterly earnings per share (EPS) without annualizing it. When you divide a stock price by a single quarter’s earnings, you get a ratio ~4x higher than the true annual P/E.

Here is the correct, annualized breakdown for Salesforce (CRM) as of today:

  • Market Capitalization: ~$152.1 Billion
  • Trailing Twelve Months (TTM) EPS: $8.63
  • Trailing P/E Ratio: ~21.5x

When calculated correctly (Price / Annual EPS), the P/E ratio is in the low 20s, not the 40s or 50s. The 20s reflect a more typical valuation range for a mature software company of Salesforce's scale.

so make chart again with correct numbers

Calling: compute - code="df_142['date'] = pd.to_datetime(df_142['date'])\ndf_144['date'] = pd.to_datetime(df_144['date'])\ndf_144 = df_144[df_144['period_type'] == 'quarterly'].sort_values('date')\ndf_144['ttm_eps'] = df_144.groupby('ticker')['eps_reported'].rolling(window=4).sum().reset_index(0, drop=True)\nmerged = pd.merge_asof(df_142.sort_values('date'), df_144[['ticker', 'date', 'ttm_eps']].sort_values('date'), on='date', by='ticker', direction='backward')\nmerged['pe_ratio'] = merged['close'] / merged['ttm_eps']\nresult = merged[['ticker', 'date', 'pe_ratio']].dropna()", dataframe_ids=[142, 144] DataFrame 147 OK result_147 (1256 rows)

Calling: show_chart - x="date", series=["pe_ratio"], dataframe_id=147, title="Salesforce (CRM) Trailing P/E Ratio (Last 5 Years)" Blob 64 DataFrame 147 OK result_147 (1256 rows)

can you call show_cahrt again

Calling: show_chart - x="date", dataframe_id=147, series=["pe_ratio"], title="Salesforce (CRM) Trailing P/E Ratio (Last 5 Years)" Blob 65 DataFrame 147 OK result_147 (1256 rows)

Data MAX

The chart for Salesforce's Trailing P/E ratio (calculated as Price divided by TTM Earnings) has been displayed above, reflecting the corrected, normalized valuation metrics you requested.

New