Could you let us know your journey into technology? What inspired you to start Competera?
I’ve always wanted to get away from my past in Consultancy. I remember how it took consultants a lot of time and money to generate the same price and promo recommendations based on econometrics, mathematical statistics and sales forecast for different retailers.
As I have a background in Engineering, I dreamed of creating a product that could do all of this with just one magical click. That’s what I had in mind when Co-founding Competera. We wanted to make it easier for end-users to do their job and help them do great without engaging consultants that require considerable time and money investment. Thanks to the advancements in AI, it has finally become real.
What is Competera and what is your differentiating technology?
Competera is a place where retail category managers can make the right pricing decisions quickly and easily without the help of consultants, analysts, and pricing architects. These managers can forecast their future sales with two clicks thanks to the power of neural networks.
What helps Competera stand out is that using our product does not require the engagement of any other team rather than category or pricing managers on the side of the retailer, ensures ten times faster time-to-value and is four times less expensive than any other solution in the market.
To compare, when hiring a consultant you’ll need to wait for a year or more to get a pool of recommendations for every particular category and some time after that to start implementing the strategy. What’s more, such recommendations are not scalable, which means you’ll need to engage consultants for every new category over and over again.
What are your customers’ biggest challenges?
Today any pricing decision is mostly based on three parameters and a set of business constraints, which in reality reflect the personal experience of a particular expert. Alternatively, as I mentioned before, category managers need to engage consultancies to make the right decisions.
But the world of retail is changing rapidly, challenging retail teams to make data-driven decisions extremely fast to create a truly rewarding customer experience. Such decisions require taking into account at least 60 factors, which is impossible without special technology like AI. That’s where AI-powered Competera jumps in.
How does Competera Pricing Platform help pricing and category managers? What other retail teams and processes can benefit from the platform, directly or indirectly?
Competera mostly helps category managers that are responsible for the performance of a particular category to make data-driven and quick pricing decisions.
In addition to category managers, we also help Marketing teams make their promotional campaigns more data-driven and profitable; product managers and their leads to easily track the efficiency of their teams and change their strategy, if necessary; CEOs to hit all the set business goals, course-correct their strategy on the fly and eventually make their businesses more agile and competitive.
How does your technology impact bottom-line results?
We influence three key business KPIs: profitability, revenue, and customer LTV.
Competera helps retailers not to gain additional profits and revenue, but stop losing their money, which has been the case for years. The loss can be blamed on the fact that prices are set for every individual item, without taking into account the interconnections between this and other products, the whereabouts of the store, and other factors. We use the power of AI to help retailers base their pricing on all the necessary data, speed up their repricing and make it more transparent.
Speaking from my experience, AI can help save up to 200 b.p. in profit margins and reduce repricing time from several hours to 15 minutes.
How does Competera’s platform provide the desired results?
We help retailers switch from econometrics-based pricing which requires manual work to a completely new level of pricing. We have combined the power of Econometrics, Mathematical statistics, and Machine Learning to help retail teams base their pricing decisions on up to 60 factors without the help from analysts and consultants and be flexible in their pricing strategies.
Do you think there is a need for Human Intelligence and Supervision in this AI-enhanced process?
I believe that any modern Technology is a co-pilot for humans. Technology like AI does not replace humans but helps them transition to a different set of tasks. Human managers need to steer the process, set and manage goals, for example, “to increase revenue” or “maintain margins,” and set constraints.
Meanwhile, technology takes on routine work and extremely complex calculations. It provides category managers with insights and possible scenarios to choose from.
Which geographies are you currently focusing on?
We have clients from 28 countries. For now, we are strengthening our positions in the UK and entering the US market.
How has retail pricing evolved?
There have been several stages of pricing evolution. The first one is cost-based pricing, which takes into account the base price and a desirable margin. It works, but it does not offer tools to scale. In a bid to receive better results, retailers naturally start looking at the performance of their competitors.
Competition-based pricing helps retailers boost sales, but fails to keep, let alone increase profit margins. This approach to pricing also leads to price and promo wars and results in extremely low prices across the whole market.
As a result, retailers seek new pricing approaches that allow them to take into account their own target profitability, brand equity, and business goals. We call it rule-based pricing. Such an approach helps retailers react to competitors’ price changes quicker and boost the rate of sales.
The next stage is portfolio-based pricing. It allows for taking into account all millions of cross-product impacts. That’s what Amazon has been doing for over a decade. When using this pricing approach, retailers know what products can be offered at much lower prices to increase traffic and what items should be priced higher to compensate for the profit margin loss. In other words, retail teams can find this healthy balance between sales and profits.
As Machine Learning algorithms are becoming more sophisticated and affordable, setting the right prices is getting faster and more effective, and requires less investment than before.
What are your predictions on the most impactful disruptions in AI-based enterprise tools for 2019-2024?
AI can process millions of data points, detect the correlation between them, see the patterns no one can see, and use all of these to offer proper insights for the right decisions.
Thus, AI has a huge potential in upgrading any industry or process — from airlines to restaurants and hotel businesses, to retail, to security, to crime prevention. It’s just a matter of time.
What’s the best advice you have ever received?
I’d like to share two pieces of advice.
Number one: you need to realize that there are two types of businesses. Those that “fly” and those that “crawl.” The “flying” companies set their prices based on their customers knowing the value of the offer and their readiness to pay for it. The “crawling” companies make cost-based pricing decisions. Knowing this helped us realize that we belong to the first type, as well as create a starting point for Competera’s positioning, selling strategies and pricing.
Number two: don’t ever get discouraged. Business is a risky venture which means that today you feel like a prince and tomorrow you feel like a pauper. It’s a seesaw. And you need to accept this, keep going and enjoy what you do. And always stay on top of the trends.
One word that best describes how you work.
Passion and vision.
Which superhero do you profoundly relate to?
Iron Man (60%) for his entrepreneurial and innovative talents and Thor (40%) for his love to others and staying true to basic human values.
Tag the one person in the industry whose answers to these questions you would love to read.
Thank you, Alexandr! That was fun and hope to see you back on MarTech Series soon.
Alexandr Galkin is CEO and Co-founder of Competera, a one-stop-shop pricing platform for enterprise retailers looking to increase revenue and stay competitive. He is a Forbes contributor, speaker at IRX, e-Commerce and RBTE conferences.
Competera offers a cloud-native platform for brick&click retailers to make optimal price and promo decisions. Powered by the idea to make retailers more productive and profitable, Competera is a reliable partner to over 100 clients across 28 countries. In 2019, the company has been ranked №1 price optimization solution by Crozdesk Buyer Guide.
The MTS Martech Interview Series is a fun Q&A style chat which we really enjoy doing with martech leaders. With inspiration from Lifehacker’s How I work interviews, the MarTech Series Interviews follows a two part format On Marketing Technology, and This Is How I Work. The format was chosen because when we decided to start an interview series with the biggest and brightest minds in martech – we wanted to get insight into two areas … one – their ideas on marketing tech and two – insights into the philosophy and methods that make these leaders tick.