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Darktrace
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== Risks to profitability == Given that new customer acquisition will be the key pillar of Darktrace’s ARR growth going forward, the efficiency of customer acquisition and the quality of customers added are key drivers of Darktrace’s profitability. The barriers to entry in segments Darktrace operates in are low, in JP Morgan's view, with several start-ups and established cybersecurity vendors targeting similar use-cases. Darktrace currently leads the network detection and response market and has seen good early success with its email product. However, given the competitive backdrop, there is a risk that customer acquisition and retention may get tougher going forward. If this were to happen, it would translate to higher customer acquisition costs and drive increased investments in existing and new product development – both of which will limit margin leverage, in JP Morgan's view. Early success in the AI-driven threat detection and response market and investment in marketing have helped Darktrace scale rapidly, delivering above-average growth (52% 2018-21 revenue CAGR); looking ahead, JP Morgan believes investor focus will shift towards how the company balances growth and profitability. Assessing this development through the lens of the ‘Rule of 40’ (revenue growth + FCF margin) is a good indicator of the progress the company is making to sustain profitable growth. JP Morgan expects the sum of revenue growth and FCF margin to dip and remain below 40% over the next couple of years, which would weigh on Darktrace's valuation compared to other cybersecurity peers that consistently beat this 40% benchmark. === Higher cloud deployments likely to pressure gross margins === This cost bucket primarily includes costs associated with deploying Darktrace software – either via physical appliances or via cloud. Costs associated with providing customer support and supplementary monitoring and response capabilities (‘concierge’ services). Darktrace does not earn any material revenue from selling physical appliances – the company considers physical appliances as its assets, with the corresponding depreciation logged either as cost of sales (for appliances deployed at contracted customer sites) or as sales and marketing expenses (for appliances used in customer acquisition, i.e. as part of the POV process). With a growing portion of cloud-hosted product sales, the portion of hosting costs will increase. The company expects the increase in hosting costs to be partly offset by a decline in appliance depreciation (substitution effect). JP Morgan models Darktrace’s cost of sales as % of revenue to increase gradually from 10% in 2021 to 12.5% in 2024.'''<br />Figure 27: Darktrace: Cost of sales as % of revenue: 2019-24E'''<ref>Source: Company data, J.P. Morgan estimates; FY ends in Jun.</ref> [[File:Figure 27.png]] === Sales & Marketing expenses likely to remain elevated === 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; * 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>''' [[File:Figure 28.png]] '''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 === 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. === Margin leverage likely to be limited through JP Morgan's forecast horizon === Non-T&E G&A expenses as % of revenue grew from 13% in 2020 to 20% in 1H22 as a result of higher public company costs post IPO. Darktrace expects G&A to tick up in 2H22 followed by decline from 2023. '''Figure 30: Non-T&E R&D expenses* as % of revenue'''<ref name=":5" /> [[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. 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> [[File:Figure 32.png]] '''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 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 === Darktrace targets steady-state adjusted EBIT margins in the mid-20s% range in the long term. This will be a function of opex components as % of revenue in the following ranges: * Cost of sales: 10-13% * Sales and marketing: 40-43% * R&D: 10-13% * G&A: 10-13% The company does not expect to hit these steady-state margin levels in the foreseeable future as it continues to prioritize new customer acquisition. '''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> [[File:Figure 35.png]] === The pursuit of growth will likely limit margin improvement === 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 ~$50m in 2022 with ~12% margin, at the high end of Darktrace’s guided range of 10-12%. Darktrace expects a steep dip in adjusted EBITDA margin in 2H22 following 24% margin in 1H22. This is driven by the following factors: * Ramp in T&E expenses; * Significant increase in facilities and office costs in 2H; * Return to normal cadence of salesforce hiring; JP Morgan expects Darktrace’s adjusted EBITDA margin to improve from 1H23 following the dip in 2H22; however, the pace of improvement is likely to be gradual as the company will continue to invest in sales and marketing to acquire new customers and in new product development as it seeks to build on its platform strategy with ‘Prevent’ and ‘Heal’ product suites. '''Figure 36: Adjusted EBITDA ($, m) and margin (%): 2019-24E<ref name=":7" />''' [[File:Figure 36.png]] '''Figure 37: Adjusted EBITDA margin (%): 1H20-2H24E<ref name=":7" />''' [[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. '''Figure 38: Revenue growth (%) + FCF growth (%)'''<ref name=":9" /> [[File:Figure 38.png]]
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