Darktrace - Revision history

95.149.241.133 at 20:03, 19 August 2022

2022-08-19T20:03:36Z

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	[[Category:Thesis]]		[[Category:Thesis]]
	[[Category:Equities]]		[[Category:Equities]]

			__INDEX__

>Louis at 16:14, 22 July 2022

2022-07-22T16:14:27Z

← Older revision		Revision as of 17:14, 22 July 2022
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	==Notes==		==Notes==
			<references />
			[[Category:Thesis]]
			[[Category:Equities]]

172.18.0.2: /* The pursuit of growth will likely limit margin improvement‌ */

2022-06-18T13:27:17Z

The pursuit of growth will likely limit margin improvement‌

>JPMorgan at 22:45, 16 June 2022

2022-06-16T22:45:04Z

← Older revision		Revision as of 23:45, 16 June 2022
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	[[File:Darktrace logo.jpg\|thumb]]		[[File:Darktrace logo.jpg\|thumb]]

	'''~~Path to sustainable profitable growth unclear~~'''		'''A global leader in cyber security technology'''

	== Summary ==		== Summary ==

>JPMorgan at 22:38, 16 June 2022

2022-06-16T22:38:32Z

>JPMorgan at 22:22, 16 June 2022

2022-06-16T22:22:56Z

← Older revision		Revision as of 23:22, 16 June 2022
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	* Lower facilities/office costs as the return to office was delayed.		* Lower facilities/office costs as the return to office was delayed.
	While the company has not quantified the impact from these factors, it notes seeing some scale efficiencies, driven by a more efficient marketing function. The majority of sales and marketing expenses (salaries + 50% sales commissions) associated with revenue generated in a given period are incurred in prior periods (during contract acquisition) – this coupled with some improvement in marketing efficiency has translated to scale efficiencies. Darktrace sees a healthy pipeline of potential new customer opportunities and stable POV conversion rates (although the company has not disclosed this metric). However, JP Morgan believes it is too early to extrapolate this trend to outer years, given the increase in competitive intensity. Wage inflation is another factor to be considered in assessing the evolution of margin going forward.'''<br />Figure 28: Non-T&E operating expenses* (total) as % of revenue<ref name=":5">Source: Company data *includes share-based comp and associated employer tax charges; FY ends in Jun.</ref>'''		While the company has not quantified the impact from these factors, it notes seeing some scale efficiencies, driven by a more efficient marketing function. The majority of sales and marketing expenses (salaries + 50% sales commissions) associated with revenue generated in a given period are incurred in prior periods (during contract acquisition) – this coupled with some improvement in marketing efficiency has translated to scale efficiencies. Darktrace sees a healthy pipeline of potential new customer opportunities and stable POV conversion rates (although the company has not disclosed this metric). However, JP Morgan believes it is too early to extrapolate this trend to outer years, given the increase in competitive intensity. Wage inflation is another factor to be considered in assessing the evolution of margin going forward.'''<br />Figure 28: Non-T&E operating expenses* (total) as % of revenue<ref name=":5">Source: Company data *includes share-based comp and associated employer tax charges; FY ends in Jun.</ref>'''

			[[File:Figure 28.png]]

	'''Figure 29: Non-T&E S&M expenses* as % of revenue<ref name=":5" />'''		'''Figure 29: Non-T&E S&M expenses* as % of revenue<ref name=":5" />'''

			[[File:Figure 29.png]]

	=== R&D intensity needs to pick up to create a sustainable moat‌ ===		=== R&D intensity needs to pick up to create a sustainable moat‌ ===
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	'''Figure 30: Non-T&E R&D expenses* as % of revenue'''<ref name=":5" />		'''Figure 30: Non-T&E R&D expenses* as % of revenue'''<ref name=":5" />

	'''Figure 31: Non-T&E G&A expenses* as % of revenue<ref name=":5" /><br />'''		[[File:Figure 30.png]]

			'''Figure 31: Non-T&E G&A expenses* as % of revenue<ref name=":5" /><br />'''[[File:Figure 31.png]]

	Darktrace reported total T&E expenses of $1.8m in 2021, down from $21m in 2020 (normalized 2020 T&E expense is $27-28m). The company reported a lower-than- expected T&E expense in 1H22 of $2.7m – with economies opening up and travel returning to normal, Darktrace expects a steep ramp in T&E expenses in 2H22, returning to a more normalized run-rate.		Darktrace reported total T&E expenses of $1.8m in 2021, down from $21m in 2020 (normalized 2020 T&E expense is $27-28m). The company reported a lower-than- expected T&E expense in 1H22 of $2.7m – with economies opening up and travel returning to normal, Darktrace expects a steep ramp in T&E expenses in 2H22, returning to a more normalized run-rate.
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	'''Figure 32: Total opex as % of revenue: 2019-24E'''<ref name=":6">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>		'''Figure 32: Total opex as % of revenue: 2019-24E'''<ref name=":6">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>

			[[File:Figure 32.png]]

	'''Figure 33: Total opex (excl. charges associated with share-based comp) as % of revenue: 2019-24E<ref name=":6" />'''		'''Figure 33: Total opex (excl. charges associated with share-based comp) as % of revenue: 2019-24E<ref name=":6" />'''

			[[File:Figure 33.png]]

	Given JP Morgan's assumptions on opex, JP Morgan models continued operating loss throughout JP Morgan's forecast horizon. Even after excluding share-based comp and associated employer tax charges, JP Morgan does not model any significant improvement in adjusted EBIT margin during JP Morgan's forecast horizon.		Given JP Morgan's assumptions on opex, JP Morgan models continued operating loss throughout JP Morgan's forecast horizon. Even after excluding share-based comp and associated employer tax charges, JP Morgan does not model any significant improvement in adjusted EBIT margin during JP Morgan's forecast horizon.
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	'''Figure 34: Adj. EBIT margin (%): 2019-24E'''<ref name=":7">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>		'''Figure 34: Adj. EBIT margin (%): 2019-24E'''<ref name=":7">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>

			[[File:Figure 34.png]]

	'''Figure 35: Adj. EBIT margin (%): Long-term steady-state model'''<ref name=":8">Source: Company data.</ref>		'''Figure 35: Adj. EBIT margin (%): Long-term steady-state model'''<ref name=":8">Source: Company data.</ref>

			[[File:Figure 35.png]]

	=== The pursuit of growth will likely limit margin improvement‌ ===		=== The pursuit of growth will likely limit margin improvement‌ ===
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	'''Figure 36: Adjusted EBITDA ($, m) and margin (%): 2019-24E<ref name=":7" />'''		'''Figure 36: Adjusted EBITDA ($, m) and margin (%): 2019-24E<ref name=":7" />'''

			[[File:Figure 36.png]]

	'''Figure 37: Adjusted EBITDA margin (%): 1H20-2H24E<ref name=":7" />'''		'''Figure 37: Adjusted EBITDA margin (%): 1H20-2H24E<ref name=":7" />'''

			[[File:Figure 37.png]]

	Early success in the AI-driven threat detection and response market has helped Darktrace scale rapidly, delivering above-average growth (52% 2018-21 revenue CAGR); however, the eventual success of the company will be determined by how the company balances growth and profitability. Assessing this development through the lens of the ‘Rule of 40’ is a good indicator of the progress the company is making to sustain profitable growth. The Rule of 40 is the principle that the sum of revenue growth and profitability measure for successful business models should exceed 40%. JP Morgan uses the sum of revenue growth and free cash flow margin (FCF calculated as cash flow from operations less tangible and intangible capex) as a gauge of the success of Darktrace’s business model. With growing competition and commoditization in the AI-driven threat detection and response market, the sum of revenue growth and free cash flow margin is likely to dip and remain below 40% over the next couple of years, in JP Morgan's view (JP Morgan models 38%/35% in 2023/24, down from 58% in 2022). JP Morgan believes that this outcome will be reflected in Darktrace’s valuation compared to other cybersecurity peers that consistently beat the 40% benchmark.		Early success in the AI-driven threat detection and response market has helped Darktrace scale rapidly, delivering above-average growth (52% 2018-21 revenue CAGR); however, the eventual success of the company will be determined by how the company balances growth and profitability. Assessing this development through the lens of the ‘Rule of 40’ is a good indicator of the progress the company is making to sustain profitable growth. The Rule of 40 is the principle that the sum of revenue growth and profitability measure for successful business models should exceed 40%. JP Morgan uses the sum of revenue growth and free cash flow margin (FCF calculated as cash flow from operations less tangible and intangible capex) as a gauge of the success of Darktrace’s business model. With growing competition and commoditization in the AI-driven threat detection and response market, the sum of revenue growth and free cash flow margin is likely to dip and remain below 40% over the next couple of years, in JP Morgan's view (JP Morgan models 38%/35% in 2023/24, down from 58% in 2022). JP Morgan believes that this outcome will be reflected in Darktrace’s valuation compared to other cybersecurity peers that consistently beat the 40% benchmark.

	'''Figure 38: Revenue growth (%) + FCF growth (%)'''<ref name=":9" />		'''Figure 38: Revenue growth (%) + FCF growth (%)'''<ref name=":9" />

			[[File:Figure 38.png]]

	== Shifting the focus to profitability‌ ==		== Shifting the focus to profitability‌ ==

>JPMorgan at 21:41, 16 June 2022

2022-06-16T21:41:37Z

Show changes

>JPMorgan at 21:25, 16 June 2022

2022-06-16T21:25:39Z

← Older revision		Revision as of 22:25, 16 June 2022
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	'''Figure 7: Customer split by contract ARR size<ref>Source: Company data; FY ends in Jun.</ref>'''		'''Figure 7: Customer split by contract ARR size<ref>Source: Company data; FY ends in Jun.</ref>'''

	[[File:Figure 7.png]]~~'''Figure 8: % of customers using more than one Darktrace product<ref>Source: Company data; FY ends in Jun.</ref>'''~~		[[File:Figure 7.png]]

	[[File:Figure 8.png]]Darktrace reported 1-year gross ARR churn of 6.4% as of end-1H22 (six-month period ending in Dec-21) vs. 7.6% exiting Jun-21. As expected, Darktrace sees higher churn among customers with contract size less than $100k in ARR. Darktrace’s 1-yr gross ARR churn is higher compared to other cybersecurity vendors (such as Crowdstrike, which reported 1-yr gross ARR churn of ~2% in FY21) given its SMB/mid-market heavy customer base. Darktrace reported net ARR retention rate of 105.1% in 1H22 (increasing from 99.1% in 2020 and 102.9% in 2021) – the increase in net ARR retention rate is a function of higher product upsell/cross-sell and stabilizing churn. Darktrace is investing in its customer success function, which should help stabilize churn and drive higher upsells/cross-sells at the point of renewal. That said, given the SMB/mid-market heavy customer base (which is characterized by higher churn compared to larger enterprise customers) and multiple products purchased at the initial point of sale (which limits the scope of cross-sells), Darktrace does not expect to see a significant improvement in net ARR retention rate going forward (the improvement, if any, is likely to be more gradual).		'''Figure 8: % of customers using more than one Darktrace product<ref>Source: Company data; FY ends in Jun.</ref>'''

			[[File:Figure 8.png]]

			Darktrace reported 1-year gross ARR churn of 6.4% as of end-1H22 (six-month period ending in Dec-21) vs. 7.6% exiting Jun-21. As expected, Darktrace sees higher churn among customers with contract size less than $100k in ARR. Darktrace’s 1-yr gross ARR churn is higher compared to other cybersecurity vendors (such as Crowdstrike, which reported 1-yr gross ARR churn of ~2% in FY21) given its SMB/mid-market heavy customer base. Darktrace reported net ARR retention rate of 105.1% in 1H22 (increasing from 99.1% in 2020 and 102.9% in 2021) – the increase in net ARR retention rate is a function of higher product upsell/cross-sell and stabilizing churn. Darktrace is investing in its customer success function, which should help stabilize churn and drive higher upsells/cross-sells at the point of renewal. That said, given the SMB/mid-market heavy customer base (which is characterized by higher churn compared to larger enterprise customers) and multiple products purchased at the initial point of sale (which limits the scope of cross-sells), Darktrace does not expect to see a significant improvement in net ARR retention rate going forward (the improvement, if any, is likely to be more gradual).

	'''Figure 9: Period-end 1-year gross ARR churn (%)<ref>Source: Company data; one-year gross ARR churn rate is defined as the ARR value of customers lost from the existing customer cohort one year prior to the measurement date, divided by the total ARR value of that existing customer cohort (this metric reflects only customer losses and does not reflect expansions or contractions); FY ends in Jun.</ref>'''		'''Figure 9: Period-end 1-year gross ARR churn (%)<ref>Source: Company data; one-year gross ARR churn rate is defined as the ARR value of customers lost from the existing customer cohort one year prior to the measurement date, divided by the total ARR value of that existing customer cohort (this metric reflects only customer losses and does not reflect expansions or contractions); FY ends in Jun.</ref>'''

>JPMorgan: /* Valuation‌ */

2022-06-16T21:23:58Z

Valuation‌

← Older revision		Revision as of 22:23, 16 June 2022
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	Accordingly, JP Morgan initiates coverage on the stock with an Underweight rating and set JP Morgan's Dec-23 price target at 400p, based on 5.5x ’23E EV/sales (calendarized), ~35% discount to its peer group median (vs. YTD average of ~25% discount). JP Morgan's choice of a higher discount vs. peer median reflects JP Morgan's view of increased competition and limited visibility on the path to achieve sustained profitable growth. On a relative basis, JP Morgan believes that there are better opportunities elsewhere to play the proactive cybersecurity theme – such as CrowdStrike (leading disruptor in endpoint security), CyberArk (Privileged Access Management leader), Tenable (leader in vulnerability management) and Varonis (user and entity behaviour analytics).		Accordingly, JP Morgan initiates coverage on the stock with an Underweight rating and set JP Morgan's Dec-23 price target at 400p, based on 5.5x ’23E EV/sales (calendarized), ~35% discount to its peer group median (vs. YTD average of ~25% discount). JP Morgan's choice of a higher discount vs. peer median reflects JP Morgan's view of increased competition and limited visibility on the path to achieve sustained profitable growth. On a relative basis, JP Morgan believes that there are better opportunities elsewhere to play the proactive cybersecurity theme – such as CrowdStrike (leading disruptor in endpoint security), CyberArk (Privileged Access Management leader), Tenable (leader in vulnerability management) and Varonis (user and entity behaviour analytics).



	'''Figure 1: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: 2017-present<ref name=":1">Source: Bloomberg Finance L.P.</ref>'''[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 10 Image 0002.png]]		'''Figure 1: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: 2017-present<ref name=":1">Source: Bloomberg Finance L.P.</ref>'''[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 10 Image 0002.png]]
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	'''Figure 4: Customer split % (by volume) by industry vertical (as of Feb-21)'''<ref name=":2">Source: Company data.</ref>		'''Figure 4: Customer split % (by volume) by industry vertical (as of Feb-21)'''<ref name=":2">Source: Company data.</ref>

			[[File:Figure 4.png]]

	'''Figure 5: Period-end number of customers<ref>Source: Company data; FY ends in Jun.</ref>'''		'''Figure 5: Period-end number of customers<ref>Source: Company data; FY ends in Jun.</ref>'''

			[[File:Figure 5.png]]

	'''Figure 6: Revenue split by geography (%)<ref>Source: Company data; revenue from customers has been attributed to the geographic market based on contractual location; FY ends in Jun.</ref>'''		'''Figure 6: Revenue split by geography (%)<ref>Source: Company data; revenue from customers has been attributed to the geographic market based on contractual location; FY ends in Jun.</ref>'''

			[[File:Figure 6.png]]

	==== Churn ====		==== Churn ====
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	'''Figure 7: Customer split by contract ARR size<ref>Source: Company data; FY ends in Jun.</ref>'''		'''Figure 7: Customer split by contract ARR size<ref>Source: Company data; FY ends in Jun.</ref>'''

			[[File:Figure 7.png]]'''Figure 8: % of customers using more than one Darktrace product<ref>Source: Company data; FY ends in Jun.</ref>'''

	~~'''~~Figure 8~~: % of customers using more than one Darktrace product<ref>Source: Company data; FY ends in Jun~~.~~</ref>'''~~		[[File:Figure 8.png]]Darktrace reported 1-year gross ARR churn of 6.4% as of end-1H22 (six-month period ending in Dec-21) vs. 7.6% exiting Jun-21. As expected, Darktrace sees higher churn among customers with contract size less than $100k in ARR. Darktrace’s 1-yr gross ARR churn is higher compared to other cybersecurity vendors (such as Crowdstrike, which reported 1-yr gross ARR churn of ~2% in FY21) given its SMB/mid-market heavy customer base. Darktrace reported net ARR retention rate of 105.1% in 1H22 (increasing from 99.1% in 2020 and 102.9% in 2021) – the increase in net ARR retention rate is a function of higher product upsell/cross-sell and stabilizing churn. Darktrace is investing in its customer success function, which should help stabilize churn and drive higher upsells/cross-sells at the point of renewal. That said, given the SMB/mid-market heavy customer base (which is characterized by higher churn compared to larger enterprise customers) and multiple products purchased at the initial point of sale (which limits the scope of cross-sells), Darktrace does not expect to see a significant improvement in net ARR retention rate going forward (the improvement, if any, is likely to be more gradual).



	Darktrace reported 1-year gross ARR churn of 6.4% as of end-1H22 (six-month period ending in Dec-21) vs. 7.6% exiting Jun-21. As expected, Darktrace sees higher churn among customers with contract size less than $100k in ARR. Darktrace’s 1-yr gross ARR churn is higher compared to other cybersecurity vendors (such as Crowdstrike, which reported 1-yr gross ARR churn of ~2% in FY21) given its SMB/mid-market heavy customer base. Darktrace reported net ARR retention rate of 105.1% in 1H22 (increasing from 99.1% in 2020 and 102.9% in 2021) – the increase in net ARR retention rate is a function of higher product upsell/cross-sell and stabilizing churn. Darktrace is investing in its customer success function, which should help stabilize churn and drive higher upsells/cross-sells at the point of renewal. That said, given the SMB/mid-market heavy customer base (which is characterized by higher churn compared to larger enterprise customers) and multiple products purchased at the initial point of sale (which limits the scope of cross-sells), Darktrace does not expect to see a significant improvement in net ARR retention rate going forward (the improvement, if any, is likely to be more gradual).

	'''Figure 9: Period-end 1-year gross ARR churn (%)<ref>Source: Company data; one-year gross ARR churn rate is defined as the ARR value of customers lost from the existing customer cohort one year prior to the measurement date, divided by the total ARR value of that existing customer cohort (this metric reflects only customer losses and does not reflect expansions or contractions); FY ends in Jun.</ref>'''		'''Figure 9: Period-end 1-year gross ARR churn (%)<ref>Source: Company data; one-year gross ARR churn rate is defined as the ARR value of customers lost from the existing customer cohort one year prior to the measurement date, divided by the total ARR value of that existing customer cohort (this metric reflects only customer losses and does not reflect expansions or contractions); FY ends in Jun.</ref>'''

			[[File:Figure 9.png]]

	'''Figure 10: Period-end net ARR retention rate (%)<ref>Source: Company data; net ARR retention rate is defined as the current ARR value for all customers that were customers one year prior to the measurement date, divided by their ARR one year prior to the measurement date (this metric reflects customer losses, expansions and contractions); FY ends in Jun.</ref>'''		'''Figure 10: Period-end net ARR retention rate (%)<ref>Source: Company data; net ARR retention rate is defined as the current ARR value for all customers that were customers one year prior to the measurement date, divided by their ARR one year prior to the measurement date (this metric reflects customer losses, expansions and contractions); FY ends in Jun.</ref>'''

			[[File:Figure 10.png]]
	=== Go-to-market ===		=== Go-to-market ===
	Darktrace sees its offerings as complementary to an enterprise’s existing security investments. The company sees a large greenfield opportunity for its products (a potential addressable customer base of >150k across industries) – accordingly, Darktrace remains focused on acquiring new customers and driving high platform adoption at the initial point of purchase.		Darktrace sees its offerings as complementary to an enterprise’s existing security investments. The company sees a large greenfield opportunity for its products (a potential addressable customer base of >150k across industries) – accordingly, Darktrace remains focused on acquiring new customers and driving high platform adoption at the initial point of purchase.
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	Given Darktrace’s strategic focus on acquiring new customers, its ARR growth is dependent on the scaling of its POV trials. This in turn is dependent on hiring of new account executives (AEs). Darktrace has indicated that ~24% of its POVs were generated exclusively by its inside sales team. The inside sales teams are incentivized based on the number of qualified meetings booked as % of closed deals. Around 28% of Darktrace’s POVs come from the partner channel.		Given Darktrace’s strategic focus on acquiring new customers, its ARR growth is dependent on the scaling of its POV trials. This in turn is dependent on hiring of new account executives (AEs). Darktrace has indicated that ~24% of its POVs were generated exclusively by its inside sales team. The inside sales teams are incentivized based on the number of qualified meetings booked as % of closed deals. Around 28% of Darktrace’s POVs come from the partner channel.

	'''Figure 11: Snapshot of Darktrace's POV-led sales cycle'''<ref name=":2" />'''<br />'''		'''Figure 11: Snapshot of Darktrace's POV-led sales cycle'''<ref name=":2" />'''<br />'''[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 17 Image 0002.png]]

	Darktrace sells its platform both directly to customers and through its channel partners (including resellers and managed security service providers). A majority of Darktrace’s sales (~65%) are generated via its direct sales personnel.		Darktrace sells its platform both directly to customers and through its channel partners (including resellers and managed security service providers). A majority of Darktrace’s sales (~65%) are generated via its direct sales personnel.
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	'''Figure 13: Network Detection & Response: CY21 Market share<ref name=":3" />'''		'''Figure 13: Network Detection & Response: CY21 Market share<ref name=":3" />'''

>JPMorgan: /* Valuation‌ */

2022-06-16T21:20:37Z

Valuation‌

← Older revision		Revision as of 22:20, 16 June 2022
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	~~'''Figure 1: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: 2017-present<ref name=":1">Source: Bloomberg Finance L.P.</ref>'''~~

			'''Figure 1: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: 2017-present<ref name=":1">Source: Bloomberg Finance L.P.</ref>'''[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 10 Image 0002.png]]

			'''Figure 2: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: Jul-21-present<ref name=":1" />'''[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 10 Image 0003.png]]
	'''Figure 2: 1-yr forward EV/sales (calendarized): Darktrace vs. peer group median: Jul-21-present<ref name=":1" />'''

	{\| class="wikitable"		{\| class="wikitable"
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	\|375		\|375
	\|}		\|}
	'''Figure 3: Valuation comparison: Darktrace vs. peer group: 2023 revenue growth + FCF margin vs. 2023 EV/sales (calendarized)'''<ref>Source: Bloomberg Finance L.P.; priced intraday as of 4th April.</ref>		'''Figure 3: Valuation comparison: Darktrace vs. peer group: 2023 revenue growth + FCF margin vs. 2023 EV/sales (calendarized)'''<ref>Source: Bloomberg Finance L.P.; priced intraday as of 4th April.</ref>[[File:20220407 JP Morgan DARK-LN Darktrace- Path to sustainable profitable growth unclear Page 11 Image 0002.png]]


	== Company Overview‌ ==		== Company Overview‌ ==
	Darktrace is a provider of proactive, AI-led threat detection and response security solutions covering on-premises network, cloud, SaaS, email, endpoints and Industrial IoT/OT environments. Darktrace’s threat detection and response approach assumes that cyber threats will succeed in breaching the organization (unlike perimeter defence technologies that seek to prevent threats from entering the organization’s digital estate) and detects and responds to these threats from within the enterprise.		Darktrace is a provider of proactive, AI-led threat detection and response security solutions covering on-premises network, cloud, SaaS, email, endpoints and Industrial IoT/OT environments. Darktrace’s threat detection and response approach assumes that cyber threats will succeed in breaching the organization (unlike perimeter defence technologies that seek to prevent threats from entering the organization’s digital estate) and detects and responds to these threats from within the enterprise.

← Older revision		Revision as of 14:27, 18 June 2022
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	=== Sales & Marketing expenses likely to remain elevated‌ ===		=== Sales & Marketing expenses likely to remain elevated‌ ===
	Darktrace has reported scale efficiencies in its core non-T&E operating costs (excluding share-based ~~comp~~ and associated employer tax charges) in recent years, with total non-T&E operating expenses as a % of revenue declining from 86% in 2020 to 74% in 1H22. This is primarily a function of some scale efficiencies the company has reported in its marketing function. Adding back share-based ~~comp~~ and associated charges, non-T&E opex as % of revenue declined from 91% in 2020 to 84% in 1H22. Margin performance in 1H22 was helped by the following one-off components (these costs will likely return through 2H22/2023):		Darktrace has reported scale efficiencies in its core non-T&E operating costs (excluding share-based compensation and associated employer tax charges) in recent years, with total non-T&E operating expenses as a % of revenue declining from 86% in 2020 to 74% in 1H22. This is primarily a function of some scale efficiencies the company has reported in its marketing function. Adding back share-based compensation and associated charges, non-T&E opex as % of revenue declined from 91% in 2020 to 84% in 1H22. Margin performance in 1H22 was helped by the following one-off components (these costs will likely return through 2H22/2023):

	* Impact from pandemic-related sales hiring delays; Darktrace is still getting back to its normal cadence of salesforce hiring and expects a catch-up in employee costs over the coming months;		* Impact from pandemic-related sales hiring delays; Darktrace is still getting back to its normal cadence of salesforce hiring and expects a catch-up in employee costs over the coming months;
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	=== R&D intensity needs to pick up to create a sustainable moat‌ ===		=== R&D intensity needs to pick up to create a sustainable moat‌ ===
	Non-T&E R&D expenses grew as % of revenue from 6% in 2020 to 8% in 1H22 (although this metric declined from 12% in 2H21). This was partly aided in 1H22 due to capitalization of share-based ~~comp~~ and related tax charges associated with development projects that met the capitalization criteria. One criticism of the Darktrace model has been the low R&D spend, both absolute and as % of revenue, compared to US cybersecurity peers. According to Darktrace, this is due to low R&D employee costs (given the company’s R&D function is primarily based in Cambridge, UK) and relatively lower development expenses needed for maintaining the self-learning cyber AI platform. The argument is that, unlike other cybersecurity companies that rely on historical threat signatures, Darktrace does not need to constantly update its platform to account for new detected threat signatures; accordingly, the company’s R&D dollars are primarily spent on new product development and research.		Non-T&E R&D expenses grew as % of revenue from 6% in 2020 to 8% in 1H22 (although this metric declined from 12% in 2H21). This was partly aided in 1H22 due to capitalization of share-based compensation and related tax charges associated with development projects that met the capitalization criteria. One criticism of the Darktrace model has been the low R&D spend, both absolute and as % of revenue, compared to US cybersecurity peers. According to Darktrace, this is due to low R&D employee costs (given the company’s R&D function is primarily based in Cambridge, UK) and relatively lower development expenses needed for maintaining the self-learning cyber AI platform. The argument is that, unlike other cybersecurity companies that rely on historical threat signatures, Darktrace does not need to constantly update its platform to account for new detected threat signatures; accordingly, the company’s R&D dollars are primarily spent on new product development and research.

	While there is substance to this argument, JP Morgan believes that new product development and platform enhancements will be increasingly important in an environment where technical and product differentiation vs. the competition narrows. This may necessitate higher R&D investment (as % of revenue), going forward, if Darktrace is to maintain its edge over competition. JP Morgan believes R&D expenses as % of revenue should tick up in 2H22 following the Cybersprint acquisition.		While there is substance to this argument, JP Morgan believes that new product development and platform enhancements will be increasingly important in an environment where technical and product differentiation vs. the competition narrows. This may necessitate higher R&D investment (as % of revenue), going forward, if Darktrace is to maintain its edge over competition. JP Morgan believes R&D expenses as % of revenue should tick up in 2H22 following the Cybersprint acquisition.
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	Darktrace reported total T&E expenses of $1.8m in 2021, down from $21m in 2020 (normalized 2020 T&E expense is $27-28m). The company reported a lower-than- expected T&E expense in 1H22 of $2.7m – with economies opening up and travel returning to normal, Darktrace expects a steep ramp in T&E expenses in 2H22, returning to a more normalized run-rate.		Darktrace reported total T&E expenses of $1.8m in 2021, down from $21m in 2020 (normalized 2020 T&E expense is $27-28m). The company reported a lower-than- expected T&E expense in 1H22 of $2.7m – with economies opening up and travel returning to normal, Darktrace expects a steep ramp in T&E expenses in 2H22, returning to a more normalized run-rate.

	Factoring-in these assumptions, JP Morgan models total opex (incl. share-based ~~comp~~ and associated tax charges) as % of revenue to tick up slightly from 97% in 2022 to 100% in 2023 (driven by the full year impact of normalized T&E expenses and normalized salesforce hiring), followed by a decline to 96% in 2024. JP Morgan models share-based ~~comp~~ and associated employer tax charges to be ~11% of revenue throughout JP Morgan's forecast period.		Factoring-in these assumptions, JP Morgan models total opex (incl. share-based compensation and associated tax charges) as % of revenue to tick up slightly from 97% in 2022 to 100% in 2023 (driven by the full year impact of normalized T&E expenses and normalized salesforce hiring), followed by a decline to 96% in 2024. JP Morgan models share-based compensation and associated employer tax charges to be ~11% of revenue throughout JP Morgan's forecast period.

	'''Figure 32: Total opex as % of revenue: 2019-24E'''<ref name=":6">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>		'''Figure 32: Total opex as % of revenue: 2019-24E'''<ref name=":6">Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref>
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	[[File:Figure 33.png]]		[[File:Figure 33.png]]

	Given JP Morgan's assumptions on opex, JP Morgan models continued operating loss throughout JP Morgan's forecast horizon. Even after excluding share-based ~~comp~~ and associated employer tax charges, JP Morgan does not model any significant improvement in adjusted EBIT margin during JP Morgan's forecast horizon.		Given JP Morgan's assumptions on opex, JP Morgan models continued operating loss throughout JP Morgan's forecast horizon. Even after excluding share-based compensation and associated employer tax charges, JP Morgan does not model any significant improvement in adjusted EBIT margin during JP Morgan's forecast horizon.

	=== Long-term steady-state model‌ ===		=== Long-term steady-state model‌ ===
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	=== The pursuit of growth will likely limit margin improvement‌ ===		=== The pursuit of growth will likely limit margin improvement‌ ===
	Adjusted EBITDA is calculated as EBITDA plus share-based ~~comp~~ and associated employer tax charges less appliance depreciation incurred as part of cost of sales (i.e. depreciation of appliances deployed at customer sites). JP Morgan models adjusted EBITDA of ~$50m in 2022 with ~12% margin, at the high end of Darktrace’s guided range of 10-12%. Darktrace expects a steep dip in adjusted EBITDA margin in 2H22 following 24% margin in 1H22. This is driven by the following factors:		Adjusted EBITDA is calculated as EBITDA plus share-based compensation and associated employer tax charges less appliance depreciation incurred as part of cost of sales (i.e. depreciation of appliances deployed at customer sites). JP Morgan models adjusted EBITDA of ~$50m in 2022 with ~12% margin, at the high end of Darktrace’s guided range of 10-12%. Darktrace expects a steep dip in adjusted EBITDA margin in 2H22 following 24% margin in 1H22. This is driven by the following factors:

	* Ramp in T&E expenses;		* Ramp in T&E expenses;